diff --git a/.github/workflows/python-app.yml b/.github/workflows/python-app.yml
index a4e8adf..8a9e0d6 100644
--- a/.github/workflows/python-app.yml
+++ b/.github/workflows/python-app.yml
@@ -24,6 +24,7 @@ jobs:
         echo /opt/minimap2-2.17_x64-linux >> $GITHUB_PATH
     - name: Install dependencies
       run: |
+        sudo apt install -qq mafft ncbi-blast+
         python -m pip install --upgrade pip pipenv
         pipenv install --dev
     - name: Test with pytest
diff --git a/Pipfile b/Pipfile
index a039031..d46c6eb 100644
--- a/Pipfile
+++ b/Pipfile
@@ -7,9 +7,10 @@ name = "pypi"
 gotoh = {subdirectory = "micall/alignment", ref = "v7.7.0", git = "https://github.com/cfe-lab/MiCall.git"}
 numpy = "==1.25.1"
 python-levenshtein = "==0.12.0"
-pandas = "==2.0.2"
+pandas = "==2.2.2"
 requests = "==2.31.0"
 pyyaml = "*"
+cfeintact = {ref = "v1.23.0", git = "https://github.com/cfe-lab/CFEIntact"}
 
 [dev-packages]
 pytest = "*"
diff --git a/Pipfile.lock b/Pipfile.lock
index 5bc34d3..bcf2914 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "73432848a2ff11546bd4d06f2cabd2c46876a987e2d0a9e8c0d379cdfd9eb4f5"
+            "sha256": "627846a347fac9a0d82e30a61f395bc23a45f30344dcf8144eeb2abebc84d9d0"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -16,107 +16,170 @@
         ]
     },
     "default": {
+        "aligntools": {
+            "git": "git+https://github.com/cfe-lab/aligntools.git",
+            "ref": "94c65f42b8b2008de4259c837eda4e9378636cb3"
+        },
+        "biopython": {
+            "hashes": [
+                "sha256:0c425a39871f652598f502671aa5f6b5125475a91333a368a47f9c611ca96db1",
+                "sha256:25f4ef193a307e403eb532e8f060b818e2d75f65803a2b0f4e645b0cae131b4e",
+                "sha256:2cb8e839ab472244b6082635ad1df67c94c05df0bd02a023103ed00ea66c4d20",
+                "sha256:2d4ed30aebd96b4aadeb1f04adce92795c696f5bd56d1fd45517b89059918dd4",
+                "sha256:2dc2e77490725060330003f73b6b7d5172f8bc160f180de5877a2e899ad999d4",
+                "sha256:3c8beded38884abae4c74cb6ce54142da670273fd0b2919bd0f84f6e34d3056b",
+                "sha256:4f39b38e7625c33384954130d90f19984e91cb5af64e2fb128603359f86884ad",
+                "sha256:507ac3956f3107e77fee362ecb048dafb5f97cbcf110012d091418430c3227c7",
+                "sha256:52b6098f47d6b90fc8a5e8579b81ee50047e9108f0976e69c891ae0c4817e42d",
+                "sha256:60fbe6f996e8a6866a42698c17e552127d99a9aab3259d6249fbaabd0e0cc7b4",
+                "sha256:61765b71f84814a1eeb55ab222f43330aa7ad3e55ab91e8b444706149c67a281",
+                "sha256:7b69d59f9a762c5bb5f77ed03f197dad05ebd702c34d2cae7be98f1f30e04089",
+                "sha256:7f4c746825721ec367c2f2d6a8cda3bc6495a1e084e5b2fbab26e9467706603f",
+                "sha256:894ee7533cca7f5f9769e2595fbe7b0dba5018f39a2170753d101a13e7585ff4",
+                "sha256:89ef3967f5a88b5bb6344bef75ae83386de53fed3966d5c8c334ad885f8db08a",
+                "sha256:9e3f7476fd81f31e048965d7be2826f018686e870d96870f440b609002953954",
+                "sha256:9fbd4b67d3e71b0d716a1712ab8b4e57981c6549ba17ce5626ffa8976d170da7",
+                "sha256:b51ef31bfb79872a182a85b4113625e1b553c024bb1586c72ac98b479f8d8fe4",
+                "sha256:b64575363bb2344073c949fd69a0bf3ea015b447aa1494e4813376855b479118",
+                "sha256:ba58a6d76288333c5f178a426116953fa68204bd0cfc401694087dd4f96d0059",
+                "sha256:c792508988fc3ccf18eaae2a826c9cd97f1c27fb55bb87bdce6a101fee9f5a0c",
+                "sha256:ca8d6a88b9a9718074b3f5b450f9ea5adf7112a7dbaed55d82d5b623f5859a01",
+                "sha256:ecff2fcf5da29b600474c0bfcdbbac0f98b25e22fe60a853d0ee798c00f7396c",
+                "sha256:ee3566f6dc3acf20e238540daf896f0af20cff531521bf41fdf5143f73e209ae",
+                "sha256:f4c1c9ad7da9eaf8d8f4515bf931a7f6548a468e7ef29b8429e31aaff2d95f4c"
+            ],
+            "markers": "python_version >= '3.9'",
+            "version": "==1.84"
+        },
         "certifi": {
             "hashes": [
-                "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7",
-                "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"
+                "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b",
+                "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"
             ],
             "markers": "python_version >= '3.6'",
-            "version": "==2023.5.7"
+            "version": "==2024.7.4"
+        },
+        "cfeintact": {
+            "git": "https://github.com/cfe-lab/CFEIntact",
+            "ref": "70031d6aff59249eb61495d2c63ae467bef6c408"
         },
         "charset-normalizer": {
             "hashes": [
-                "sha256:04e57ab9fbf9607b77f7d057974694b4f6b142da9ed4a199859d9d4d5c63fe96",
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-                "sha256:1000fba1057b92a65daec275aec30586c3de2401ccdcd41f8a5c1e2c87078706",
-                "sha256:1249cbbf3d3b04902ff081ffbb33ce3377fa6e4c7356f759f3cd076cc138d020",
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             ],
             "markers": "python_full_version >= '3.7.0'",
-            "version": "==3.2.0"
+            "version": "==3.3.2"
+        },
+        "click": {
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+                "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28",
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+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==8.1.7"
         },
         "gotoh": {
             "git": "https://github.com/cfe-lab/MiCall.git",
+            "markers": "python_version >= '3.8' and python_version < '4.0'",
             "ref": "f1687e7b7c7f1f3a6f3cb63107f1cf9b2b210f26",
             "subdirectory": "micall/alignment"
         },
         "idna": {
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             "markers": "python_version >= '3.5'",
-            "version": "==3.4"
+            "version": "==3.7"
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         "numpy": {
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@@ -147,46 +210,52 @@
                 "sha256:fd67b306320dcadea700a8f79b9e671e607f8696e98ec255915c0c6d6b818503"
             ],
             "index": "pypi",
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             "version": "==1.25.1"
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-            "version": "==2.0.2"
+            "markers": "python_version >= '3.9'",
+            "version": "==2.2.2"
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         "python-dateutil": {
             "hashes": [
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-                "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"
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-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2'",
-            "version": "==2.8.2"
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
+            "version": "==2.9.0.post0"
         },
         "python-levenshtein": {
             "hashes": [
@@ -197,14 +266,16 @@
         },
         "pytz": {
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-                "sha256:1d8ce29db189191fb55338ee6d0387d82ab59f3d00eac103412d64e0ebd0c588",
-                "sha256:a151b3abb88eda1d4e34a9814df37de2a80e301e68ba0fd856fb9b46bfbbbffb"
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+                "sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319"
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-            "version": "==2023.3"
+            "version": "==2024.1"
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         "pyyaml": {
             "hashes": [
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@@ -212,7 +283,10 @@
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                 "sha256:28c119d996beec18c05208a8bd78cbe4007878c6dd15091efb73a30e90539696",
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                 "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486",
@@ -220,11 +294,15 @@
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                 "sha256:69b023b2b4daa7548bcfbd4aa3da05b3a74b772db9e23b982788168117739938",
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                 "sha256:81e0b275a9ecc9c0c0c07b4b90ba548307583c125f54d5b6946cfee6360c733d",
+                "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28",
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                 "sha256:9eb6caa9a297fc2c2fb8862bc5370d0303ddba53ba97e71f08023b6cd73d16a8",
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@@ -237,7 +315,9 @@
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@@ -246,6 +326,7 @@
                 "sha256:fd66fc5d0da6d9815ba2cebeb4205f95818ff4b79c3ebe268e75d961704af52f"
             ],
             "index": "pypi",
+            "markers": "python_version >= '3.6'",
             "version": "==6.0.1"
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@@ -254,115 +335,140 @@
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             ],
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+            "markers": "python_version >= '3.7'",
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@@ -374,27 +480,28 @@
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+                "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"
             ],
-            "markers": "python_version >= '3.7'",
-            "version": "==23.1"
+            "markers": "python_version >= '3.8'",
+            "version": "==24.1"
         },
         "pluggy": {
             "hashes": [
-                "sha256:c2fd55a7d7a3863cba1a013e4e2414658b1d07b6bc57b3919e0c63c9abb99849",
-                "sha256:d12f0c4b579b15f5e054301bb226ee85eeeba08ffec228092f8defbaa3a4c4b3"
+                "sha256:2cffa88e94fdc978c4c574f15f9e59b7f4201d439195c3715ca9e2486f1d0cf1",
+                "sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669"
             ],
-            "markers": "python_version >= '3.7'",
-            "version": "==1.2.0"
+            "markers": "python_version >= '3.8'",
+            "version": "==1.5.0"
         },
         "pytest": {
             "hashes": [
-                "sha256:78bf16451a2eb8c7a2ea98e32dc119fd2aa758f1d5d66dbf0a59d69a3969df32",
-                "sha256:b4bf8c45bd59934ed84001ad51e11b4ee40d40a1229d2c79f9c592b0a3f6bd8a"
+                "sha256:4ba08f9ae7dcf84ded419494d229b48d0903ea6407b030eaec46df5e6a73bba5",
+                "sha256:c132345d12ce551242c87269de812483f5bcc87cdbb4722e48487ba194f9fdce"
             ],
             "index": "pypi",
-            "version": "==7.4.0"
+            "markers": "python_version >= '3.8'",
+            "version": "==8.3.2"
         },
         "tomli": {
             "hashes": [
diff --git a/README.md b/README.md
index fa27f8d..718ae86 100644
--- a/README.md
+++ b/README.md
@@ -4,6 +4,7 @@
 1. minimap2 (https://github.com/lh3/minimap2) (must be available via commandline)
 2. blast tools (ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/)
 3. R and RSCRIPT (https://www.r-project.org/)
+4. mafft (https://mafft.cbrc.jp/alignment/software/)
 
 ### Singularity builds
 * Build all singularity images inside of the `simages` folder
diff --git a/Singularity b/Singularity
index d938b8e..4a91529 100644
--- a/Singularity
+++ b/Singularity
@@ -3,7 +3,7 @@ Bootstrap: docker
 From: ubuntu:22.04
 
 %help
-    Search proviral consensus sequences for primers, then use HIVSeqinR to
+    Search proviral consensus sequences for primers, then use HIVIntact to
     decide if the genomes are complete.
 
     This Singularity container can be run on Kive: http://cfe-lab.github.io/Kive
@@ -13,7 +13,7 @@ From: ubuntu:22.04
     MAINTAINER BC CfE in HIV/AIDS https://github.com/cfe-lab/
     KIVE_INPUTS sample_info_csv contigs_csv conseqs_csv cascade_csv
     KIVE_OUTPUTS outcome_summary_csv conseqs_primers_csv contigs_primers_csv \
-        table_precursor_csv proviral_landscape_csv hivseqinr_results_tar
+        table_precursor_csv proviral_landscape_csv detailed_results_tar
     KIVE_THREADS 1
     KIVE_MEMORY 6000
 
@@ -28,6 +28,9 @@ From: ubuntu:22.04
         fontconfig libbz2-dev liblzma-dev libssl-dev \
         libffi-dev libsqlite3-dev
 
+    echo ===== Installing MAFFT ===== >/dev/null
+    apt-get install -y mafft
+
     echo ===== Installing Python ===== >/dev/null
     apt-get install -y python3 python3-pip
 
@@ -41,12 +44,6 @@ From: ubuntu:22.04
     echo ===== Installing minimap2 ===== >/dev/null
     apt-get install -y minimap2
 
-    echo ===== Installing hivseqinr ===== >/dev/null
-    apt-get install -y libz-dev libcurl4-openssl-dev libxml2-dev
-    DEBIAN_FRONTEND=noninteractive apt-get install --no-install-recommends -y r-base
-    Rscript /opt/primer_finder/gene_splicer/configure_r.sh
-    python3 -m gene_splicer.hivseqinr /opt/hivseqinr
-
     # Clean up
     apt-get remove -y wget git build-essential
 
@@ -54,4 +51,4 @@ From: ubuntu:22.04
     export LANG=en_US.UTF-8
 
 %runscript
-    gene_splicer_sample --hivseqinr /opt/hivseqinr "$@"
+    gene_splicer_sample --hivintact "$@"
diff --git a/gene_splicer/landscapes.py b/gene_splicer/landscapes.py
new file mode 100644
index 0000000..9da65e7
--- /dev/null
+++ b/gene_splicer/landscapes.py
@@ -0,0 +1,222 @@
+import csv
+import logging
+import os
+import re
+import typing
+from typing import TextIO, Mapping, Dict, Set, List, Iterable, Tuple
+import argparse
+import sys
+
+import json
+import shutil
+import subprocess as sp
+import glob
+from pathlib import Path
+from csv import DictWriter, DictReader
+from itertools import groupby
+from operator import itemgetter
+
+from gene_splicer.utils import (
+    iterate_hivintact_verdicts_1,
+    iterate_hivseqinr_verdicts_1,
+    LEFT_PRIMER_END, RIGHT_PRIMER_START,
+)
+
+
+logger = logging.getLogger(__name__)
+
+
+def generate_proviral_landscape_csv_1_cont(blastn_reader: csv.DictReader,
+                                           landscape_writer: csv.DictWriter,
+                                           verdicts: Mapping[str, str],
+                                           ) -> None:
+
+    for row in blastn_reader:
+        if row['qseqid'] in ['8E5LAV', 'HXB2']:
+            # skip the positive control rows
+            continue
+
+        ref_start = int(row['sstart'])
+        ref_end = int(row['send'])
+        if ref_end <= LEFT_PRIMER_END or ref_start >= RIGHT_PRIMER_START:
+            # skip unspecific matches of LTR at start and end
+            continue
+
+        qseqid = row['qseqid']
+        try:
+            [run_name, sample_name, _, _] = qseqid.split('::')
+        except ValueError:
+            [run_name, sample_name] = [None, qseqid]
+
+        is_inverted = ''
+        if ref_end < ref_start:
+            # automatically recognize inverted regions
+            new_end = ref_start
+            ref_start = ref_end
+            ref_end = new_end
+            is_inverted = 'yes'
+
+        verdict = verdicts[qseqid]
+        is_defective = verdict != 'Intact'
+        landscape_entry = {'ref_start': ref_start,
+                           'ref_end': ref_end,
+                           'samp_name': sample_name,
+                           'run_name': run_name,
+                           'is_inverted': is_inverted,
+                           'is_defective': is_defective,
+                           'defect': verdict,
+                           }
+
+        landscape_writer.writerow(landscape_entry)
+
+
+def get_hivintact_verdicts_1_map(details_dir: Path) -> Mapping[str, str]:
+    ret: Dict[str, str] = {}
+
+    for [qseqid, verdict] in iterate_hivintact_verdicts_1(details_dir):
+        ret[qseqid] = verdict
+
+    return ret
+
+
+def get_hivseqinr_verdicts_1_map(details_dir: Path) -> Mapping[str, str]:
+    ret: Dict[str, str] = {}
+
+    for [qseqid, verdict] in iterate_hivseqinr_verdicts_1(details_dir):
+        ret[qseqid] = verdict
+
+    return ret
+
+
+def generate_proviral_landscape_csv_1(landscape_writer: csv.DictWriter,
+                                      details_dir: Path,
+                                      ) -> None:
+    is_hivintact = (details_dir / "holistic.csv").exists()
+    if is_hivintact:
+        verdicts = get_hivintact_verdicts_1_map(details_dir)
+        blastn_path = details_dir / "blast.csv"
+    else:
+        verdicts = get_hivseqinr_verdicts_1_map(details_dir)
+        blastn_path = details_dir / "Results_Intermediate" / "Output_Blastn_HXB2MEGA28_tabdelim.txt"
+
+    with blastn_path.open() as blastn_file:
+        if is_hivintact:
+            blastn_reader = DictReader(blastn_file)
+        else:
+            blastn_columns = ['qseqid',
+                              'qlen',
+                              'sseqid',
+                              'sgi',
+                              'slen',
+                              'qstart',
+                              'qend',
+                              'sstart',
+                              'send',
+                              'evalue',
+                              'bitscore',
+                              'length',
+                              'pident',
+                              'nident',
+                              'btop',
+                              'stitle',
+                              'sstrand']
+            blastn_reader = DictReader(blastn_file, fieldnames=blastn_columns, delimiter='\t')
+
+        return generate_proviral_landscape_csv_1_cont(
+            blastn_reader,
+            landscape_writer,
+            verdicts,
+        )
+
+
+def generate_proviral_landscape_csv(outpath: Path, is_hivintact: bool):
+    proviral_landscape_csv = os.path.join(outpath, 'proviral_landscape.csv')
+
+    if is_hivintact:
+        subpath = 'hivintact*'
+    else:
+        subpath = 'hivseqinr*'
+
+    landscape_columns = ['samp_name', 'run_name', 'ref_start', 'ref_end', 'defect', 'is_inverted', 'is_defective']
+    with open(proviral_landscape_csv, 'w') as landscape_file:
+        landscape_writer = csv.DictWriter(landscape_file, fieldnames=landscape_columns)
+        landscape_writer.writeheader()
+
+        for details_dir in outpath.glob(subpath):
+            generate_proviral_landscape_csv_1(landscape_writer, details_dir)
+
+
+class UserError(RuntimeError):
+    def __init__(self, fmt: str, *fmt_args: object):
+        self.fmt = fmt
+        self.fmt_args = fmt_args
+        self.code = 1
+
+
+def dir_path(string: str) -> Path:
+    if os.path.exists(string) and os.path.isdir(string):
+        return Path(string)
+    else:
+        raise UserError("Path %r does not exist or is not a directory.", string)
+
+
+def cli_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(description="Generate Proviral Landscape CSV.")
+
+    parser.add_argument("--details_dir", type=dir_path, required=True,
+                        help="Directory containing details files for verdicts.")
+
+    parser.add_argument("--output", type=argparse.FileType("wt"), required=True,
+                        help="Output CSV file for proviral landscape.")
+
+    verbosity_group = parser.add_mutually_exclusive_group()
+    verbosity_group.add_argument('--verbose', action='store_true',
+                                 help='Increase output verbosity.')
+    verbosity_group.add_argument('--no-verbose', action='store_true',
+                                 help='Normal output verbosity.', default=True)
+    verbosity_group.add_argument('--debug', action='store_true',
+                                 help='Maximum output verbosity.')
+    verbosity_group.add_argument('--quiet', action='store_true',
+                                 help='Minimize output verbosity.')
+
+    return parser
+
+
+def main(argv: list) -> int:
+    parser = cli_parser()
+    args = parser.parse_args(argv)
+    if args.quiet:
+        logger.setLevel(logging.ERROR)
+    elif args.verbose:
+        logger.setLevel(logging.INFO)
+    elif args.debug:
+        logger.setLevel(logging.DEBUG)
+    else:
+        logger.setLevel(logging.WARN)
+
+    logger.debug("Start.")
+
+    fieldnames = ['ref_start', 'ref_end', 'samp_name', 'run_name', 'is_inverted', 'is_defective', 'defect']
+
+    landscape_writer = csv.DictWriter(args.output, fieldnames=fieldnames)
+    landscape_writer.writeheader()
+    generate_proviral_landscape_csv_1(landscape_writer, args.details_dir)
+
+    logger.debug("Done.")
+    return 0
+
+
+if __name__ == '__main__':
+    try:
+        rc = main(sys.argv[1:])
+    except BrokenPipeError:
+        logger.debug("Broken pipe.")
+        rc = 0
+    except KeyboardInterrupt:
+        logger.debug("Interrupted.")
+        rc = 1
+    except UserError as e:
+        logger.fatal(e.fmt, *e.fmt_args)
+        rc = e.code
+
+    sys.exit(rc)
diff --git a/gene_splicer/primer_finder.py b/gene_splicer/primer_finder.py
index dbb741e..ad3232a 100644
--- a/gene_splicer/primer_finder.py
+++ b/gene_splicer/primer_finder.py
@@ -1,10 +1,12 @@
 import re
+import subprocess
 from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter, FileType
 from csv import DictReader, DictWriter
 from itertools import groupby
 from operator import itemgetter
 import os
 from tarfile import TarFile
+import cfeintact
 
 import pandas as pd
 from pathlib import Path
@@ -77,6 +79,9 @@ def parse_args():
                         help="Path to HIVSeqinR source code, or download "
                              "destination. HIVSeqinR will be skipped if this "
                              "isn't given.")
+    parser.add_argument('--hivintact',
+                        action='store_true',
+                        help="Launch the HIVIntact analysis.")
     parser.add_argument(
         '--nodups',
         action='store_false',
@@ -386,8 +391,8 @@ def add_primers(row):
 def remove_primers(row):
     # Strip the primers out, convert index values from floats.
     newseq = row.sequence[
-             int(row.fwd_sample_primer_size + row.fwd_sample_primer_start)
-             :-int(row.rev_sample_primer_size + row.rev_sample_primer_start)]
+             int(row.fwd_sample_primer_size + row.fwd_sample_primer_start):
+             -int(row.rev_sample_primer_size + row.rev_sample_primer_start)]
     row.sequence = newseq
     return row
 
@@ -422,6 +427,13 @@ def archive_hivseqinr_results(working_path: Path,
         archive.add(result_path, result_path.name)
 
 
+def archive_hivintact_results(working_path: Path,
+                              hivintact_results_tar: typing.IO):
+    archive = TarFile(fileobj=hivintact_results_tar, mode='w')
+    for result_path in working_path.iterdir():
+        archive.add(result_path, result_path.name)
+
+
 def run(contigs_csv,
         conseqs_csv,
         cascade_csv,
@@ -433,7 +445,9 @@ def run(contigs_csv,
         sample_size=50,
         force_all_proviral=False,
         default_sample_name: str = None,
-        hivseqinr_results_tar: typing.IO = None):
+        hivseqinr_results_tar: typing.IO = None,
+        run_hivintact: bool = False,
+        hivintact_results_tar: typing.IO = None):
     all_samples = utils.get_samples_from_cascade(cascade_csv,
                                                  default_sample_name)
 
@@ -517,6 +531,36 @@ def run(contigs_csv,
                 if hivseqinr_results_tar is not None:
                     archive_hivseqinr_results(working_path,
                                               hivseqinr_results_tar)
+            if run_hivintact:
+                working_path = outpath / f'hivintact_{i}'
+                log_file_path = working_path / 'hiv-intact.log'
+                os.makedirs(working_path, exist_ok=True)
+
+                logger = cfeintact.logger
+                file_handler = logging.FileHandler(log_file_path)
+                logger.addHandler(file_handler)
+
+                cfeintact.check(
+                    working_dir=working_path,
+                    input_file=str(no_primers_fasta),
+                    subtype="B",
+                    check_packaging_signal=True,
+                    check_rre=True,
+                    check_major_splice_donor_site=True,
+                    check_hypermut=True,
+                    check_long_deletion=True,
+                    check_nonhiv=True,
+                    check_scramble=True,
+                    check_internal_inversion=True,
+                    check_unknown_nucleotides=True,
+                    check_small_orfs=True,
+                    check_distance=False,
+                    output_csv=True,
+                )
+
+                if hivintact_results_tar is not None:
+                    archive_hivintact_results(working_path,
+                                              hivintact_results_tar)
             files.append(no_primers_fasta)
     return files
 
@@ -531,7 +575,8 @@ def main():
                       hivseqinr=args.hivseqinr,
                       nodups=args.nodups,
                       split=args.split,
-                      sample_size=args.sample_size)
+                      sample_size=args.sample_size,
+                      run_hivintact=args.hivintact)
     return {'fasta_files': fasta_files, 'args': args}
 
 
diff --git a/gene_splicer/primer_finder_class.py b/gene_splicer/primer_finder_class.py
index d5f8cd5..a4f5cf9 100644
--- a/gene_splicer/primer_finder_class.py
+++ b/gene_splicer/primer_finder_class.py
@@ -144,7 +144,7 @@ def get_slices(self):
             hxb2_slice = utils.hxb2[self.hxb2_start -
                                     self.validation_size:self.hxb2_end]
         if len(sample_slice) == 0:
-            logger.debug(\
+            logger.debug(
                 'Sample slice size is 0! \n'
                 f'start: {self.start} \n'
                 f'end: {self.end} \n'
diff --git a/gene_splicer/sample.py b/gene_splicer/sample.py
index 5e49fb9..d00e7fa 100644
--- a/gene_splicer/sample.py
+++ b/gene_splicer/sample.py
@@ -7,6 +7,7 @@
 import gene_splicer.gene_splicer as gene_splicer
 import gene_splicer.primer_finder as primer_finder
 import gene_splicer.utils as utils
+import gene_splicer.landscapes as landscapes
 
 
 def parse_args():
@@ -43,8 +44,9 @@ def parse_args():
     parser.add_argument('proviral_landscape_csv',
                         help='Data for proviral landscape plot',
                         type=FileType('w'))
-    parser.add_argument('hivseqinr_results_tar',
-                        help="Archive file with HIVSeqinR's final results folder.",
+    parser.add_argument('detailed_results_tar',
+                        help="Archive file with HIVSeqinR's final results "
+                             "folder, or HIVIntact's results.",
                         type=FileType('wb'))
     parser.add_argument(
         '-p',
@@ -57,6 +59,9 @@ def parse_args():
                         help="Path to HIVSeqinR source code, or download "
                              "destination. HIVSeqinR will be skipped if this "
                              "isn't given.")
+    parser.add_argument('--hivintact',
+                        action='store_true',
+                        help="Launch the HIVIntact analysis.")
     parser.add_argument(
         '--nodups',
         action='store_false',
@@ -69,7 +74,7 @@ def parse_args():
         help='To avoid memory issues in hivseqinr, split the resulting '
              'qc-passed sequences into this number of fastas, each will be '
              'processed sequentially and then all will be merged into the '
-             'final result')
+             'final result. Obsolete for HIVIntact.')
     return parser.parse_args()
 
 
@@ -88,10 +93,16 @@ def main():
         info_reader = DictReader(args.sample_info_csv)
         sample_info: dict = next(info_reader)
     run_name = sample_info.get('run_name', 'kive_run')
+    if args.hivintact:
+        hivseqinr_results_tar = None
+        hivintact_results_tar = args.detailed_results_tar
+    else:
+        hivseqinr_results_tar = args.detailed_results_tar
+        hivintact_results_tar = None
     fasta_files = primer_finder.run(contigs_csv=args.contigs_csv,
                                     conseqs_csv=args.conseqs_csv,
                                     cascade_csv=args.cascade_csv,
-                                    hivseqinr_results_tar=args.hivseqinr_results_tar,
+                                    hivseqinr_results_tar=hivseqinr_results_tar,
                                     name=run_name,
                                     outpath=outpath,
                                     hivseqinr=args.hivseqinr,
@@ -99,11 +110,13 @@ def main():
                                     split=args.split,
                                     sample_size=args.sample_size,
                                     force_all_proviral=True,
-                                    default_sample_name=sample_info['sample'])
+                                    default_sample_name=sample_info['sample'],
+                                    run_hivintact=args.hivintact,
+                                    hivintact_results_tar=hivintact_results_tar)
     for file in fasta_files:
         gene_splicer.run(file, outdir=outpath)
     utils.generate_table_precursor(name=run_name, outpath=outpath)
-    utils.generate_proviral_landscape_csv(outpath)
+    landscapes.generate_proviral_landscape_csv(outpath, is_hivintact=args.hivintact)
     copy_output(outpath / 'outcome_summary.csv', args.outcome_summary_csv)
     copy_output(outpath / (run_name + '_conseqs_primer_analysis.csv'),
                 args.conseqs_primers_csv)
diff --git a/gene_splicer/study_summary.py b/gene_splicer/study_summary.py
index 74a5652..45efe1f 100644
--- a/gene_splicer/study_summary.py
+++ b/gene_splicer/study_summary.py
@@ -43,6 +43,10 @@ def parse_args():
                              'the runs in samples_csv. Any samples not found '
                              'in samples.csv will guess the participant id '
                              'from the first part of the sample name.')
+    parser.add_argument('--hivintact',
+                        action='store_true',
+                        help="Launch the HIVIntact analysis instead of "
+                             "HIVSeqinR.")
     return parser.parse_args()
 
 
@@ -197,7 +201,7 @@ def write_warnings(self, report_file: typing.TextIO, limit: int = None):
                   file=report_file)
 
 
-def run_gene_splicer(run_path: Path, outcome_folder: Path):
+def run_gene_splicer(run_path: Path, outcome_folder: Path, run_hivintact: bool):
     version_results_path = run_path / 'Results' / 'version_7.14'
     assert version_results_path.exists(), version_results_path
     denovo_path = version_results_path / 'denovo'
@@ -214,11 +218,14 @@ def run_gene_splicer(run_path: Path, outcome_folder: Path):
     pipeline_args = [python_path,
                      '-m', 'gene_splicer.pipeline',
                      '--outpath', str(outcome_folder),
-                     '--hivseqinr', str(hivseqinr_path),
                      contigs_path,
                      conseq_path,
                      cascade_path,
                      short_run_name]
+    if run_hivintact:
+        pipeline_args.append('--hivintact')
+    else:
+        pipeline_args.append(f'--hivseqinr={hivseqinr_path}')
     try:
         with log_path.open('w') as log_file:
             run(pipeline_args,
@@ -259,7 +266,7 @@ def main():
                 print('Missing denovo results:', run_path)
                 continue
             else:
-                run_gene_splicer(run_path, outcome_path.parent)
+                run_gene_splicer(run_path, outcome_path.parent, args.hivintact)
                 assert outcome_path.exists(), outcome_path
                 print('.', end='', flush=True)
                 dots_printed = True
diff --git a/gene_splicer/utils.py b/gene_splicer/utils.py
index b01b5bd..91cb81a 100644
--- a/gene_splicer/utils.py
+++ b/gene_splicer/utils.py
@@ -3,14 +3,18 @@
 import os
 import re
 import typing
+from typing import TextIO, Mapping, Dict, Set, List, Iterable, Tuple
 
 import yaml
+import json
 import shutil
 import subprocess as sp
 import pandas as pd
 import glob
 from pathlib import Path
 from csv import DictWriter, DictReader
+from itertools import groupby
+from operator import itemgetter
 
 logger = logging.getLogger(__name__)
 
@@ -97,9 +101,9 @@ def csv_to_bed(csvfile, target_name='HXB2', offset_start=0, offset_stop=0):
                 })
 
 
-def split_cigar(row):
+def split_cigar(string):
     pattern = re.compile(r'(\d+)([A-Z])')
-    cigar = re.findall(pattern, row[5])
+    cigar = re.findall(pattern, string)
     return cigar
 
 
@@ -210,11 +214,12 @@ def modify_annot(annot):
 
 def splice_genes(query, target, samfile, annotation):
     results = {}
-    for i, row in samfile.iterrows():
+    for i, row in enumerate(samfile):
         # Subtract 1 to convert target position to zero-base
         target_pos = int(row[3]) - 1
         query_pos = None
-        for size, op in row['cigar']:
+        cigar = row[5]
+        for size, op in split_cigar(cigar):
             size = int(size)
             # logger.debug(f'size: {size}, op: {op}')
             # logger.debug(f'target_pos: {target_pos}, query_pos: {query_pos}')
@@ -273,11 +278,12 @@ def coords_to_genes(coords, query):
 def splice_aligned_genes(query, target, samfile, annotation):
     results = {}
     sequences = {}
-    for i, row in samfile.iterrows():
+    for i, row in enumerate(samfile):
         # Subtract 1 to convert target position to zero-base
         target_pos = int(row[3]) - 1
         query_pos = None
-        for size, op in row['cigar']:
+        cigar = row[5]
+        for size, op in split_cigar(cigar):
             # print(f'size: {size}, op: {op}')
             # print(f'target_pos: {target_pos}, query_pos: {query_pos}')
             size = int(size)
@@ -330,9 +336,17 @@ def splice_aligned_genes(query, target, samfile, annotation):
     return results, sequences
 
 
-def load_samfile(samfile_path):
-    result = pd.read_table(samfile_path, skiprows=2, header=None)
-    result['cigar'] = result.apply(split_cigar, axis=1)
+def load_samfile(samfile_path: Path) -> List[List[str]]:
+    with open(samfile_path, 'r') as file:
+        reader = csv.reader(file, delimiter='\t')
+
+        result = []
+        for row in reader:
+            # Skip header lines (lines starting with '@')
+            if row[0].startswith('@'):
+                continue
+            result.append(row)
+
     return result
 
 
@@ -390,6 +404,92 @@ def align(target_seq,
     else:
         return alignment_path
 
+HIVINTACT_ERRORS_TABLE = [
+    'UnknownNucleotide',
+    'NonHIV',
+    'LongDeletion',
+    'InternalInversion',
+    'Scramble',
+    'APOBECHypermutation',
+    'MajorSpliceDonorSiteMutated',
+    'PackagingSignalDeletion',
+    'PackagingSignalNotComplete',
+    'RevResponseElementDeletion',
+    'MisplacedORF',
+    'WrongORFNumber',
+    'Deletion',
+    'Insertion',
+    'InternalStop',
+    'Frameshift',
+    'MutatedStopCodon',
+    'MutatedStartCodon',
+    'SequenceDivergence',
+    ]
+
+def iterate_hivintact_verdicts_1(directory: Path, intact: Set[str] = set()) -> Iterable[Tuple[str, str]]:
+    intact = set()
+
+    def get_verdict(SEQID: str, all_defects) -> Tuple[str, str]:
+        if all_defects:
+            ordered = sorted(all_defects, key=HIVINTACT_ERRORS_TABLE.index)
+            verdict = ordered[0]
+        else:
+            verdict = "Intact"
+
+        return (SEQID, verdict)
+
+    with open(os.path.join(directory, 'holistic.csv'), 'r') as f:
+        reader = csv.DictReader(f)
+        for row in reader:
+            if row["intact"] == "True":
+                intact.add(row["qseqid"])
+                SEQID = row["qseqid"]
+                yield get_verdict(SEQID, all_defects=[])
+
+    with open(os.path.join(directory, 'defects.csv'), 'r') as f:
+        reader = csv.DictReader(f)
+        grouped = groupby(reader, key=itemgetter('qseqid'))
+        for sequence_name, defects in grouped:
+            if sequence_name not in intact:
+                all_defects = [defect['code'] for defect in defects]
+                yield get_verdict(sequence_name, all_defects)
+
+
+def iterate_hivintact_verdicts(outpath: Path) -> Iterable[Tuple[str, str]]:
+    intact: Set[str] = set()
+
+    for directory in outpath.glob('hivintact*'):
+        yield from iterate_hivintact_verdicts_1(directory, intact)
+
+
+def get_hivintact_verdicts(name, outpath):
+    column_names = ['SEQID', 'MyVerdict']
+    data = iterate_hivintact_verdicts(outpath)
+    return pd.DataFrame(data, columns=column_names)
+
+
+def iterate_hivseqinr_verdicts_1(directory: Path) -> Iterable[Tuple[str, str]]:
+    path = directory / 'Output_MyBigSummary_DF_FINAL.csv'
+    if not path.is_file():
+        return
+
+    with path.open() as fd:
+        reader = csv.DictReader(fd)
+        for row in reader:
+            yield (row["SEQID"], row["MyVerdict"])
+
+
+def iterate_hivseqinr_verdicts(outpath: Path) -> Iterable[Tuple[str, str]]:
+    seqinr_paths = outpath.glob('hivseqinr*/Results_Final/Output_MyBigSummary_DF_FINAL.csv')
+    for path in seqinr_paths:
+        yield from iterate_hivseqinr_verdicts_1(path)
+
+
+def get_hivseqinr_verdicts(name, outpath):
+    column_names = ['SEQID', 'MyVerdict']
+    data = iterate_hivseqinr_verdicts(outpath)
+    return pd.DataFrame(data, columns=column_names)
+
 
 def generate_table_precursor(name, outpath, add_columns=None):
     # Output csv
@@ -398,24 +498,21 @@ def generate_table_precursor(name, outpath, add_columns=None):
     # Load filtered sequences
     filtered_path = outpath / (name + '_filtered.csv')
     filtered = pd.read_csv(filtered_path)
-    # Load hivseqinr data
-    seqinr_paths = glob.glob(
-        str(outpath / 'hivseqinr*' / 'Results_Final' /
-            'Output_MyBigSummary_DF_FINAL.csv'))
-    parts = []
-    for path in seqinr_paths:
-        if not os.path.isfile(path):
-            continue
-        part = pd.read_csv(path)
-        parts.append(part)
-    # seqinr = pd.read_csv(seqinr_path)
+    # Load hivseqinr data or HIVIntact results
+
+    if any(outpath.glob('hivintact*')):
+        results = get_hivintact_verdicts(name, outpath)
+    elif any(outpath.glob('hivseqinr*')):
+        results = get_hivseqinr_verdicts(name, outpath)
+    else:
+        raise RuntimeError("Neither HIVIntact nor HIVSeqinR directory exists.")
+
     try:
-        seqinr = pd.concat(parts)
         # Assign new columns based on split
-        seqinr[['name', 'sample', 'reference',
-                'seqtype']] = seqinr['SEQID'].str.split('::', expand=True)
+        results[['name', 'sample', 'reference',
+                'seqtype']] = results['SEQID'].str.split('::', expand=True)
         # Merge
-        merged = seqinr.merge(filtered, on='sample')
+        merged = results.merge(filtered, on='sample')
     except ValueError:
         with precursor_path.open('w') as output_file:
             writer = DictWriter(output_file,
@@ -448,7 +545,7 @@ def generate_table_precursor(name, outpath, add_columns=None):
     if add_columns:
         for key, val in add_columns.items():
             merged[key] = val
-    if parts:
+    if not results.empty:
         merged[['sample', 'sequence', 'MyVerdict'] + genes_of_interest].to_csv(
             precursor_path, index=False)
     else:
@@ -497,89 +594,18 @@ def generate_table_precursor_2(hivseqinr_resultsfile, filtered_file,
     return table_precursorfile
 
 
-def generate_proviral_landscape_csv(outpath):
-    proviral_landscape_csv = os.path.join(outpath, 'proviral_landscape.csv')
-    landscape_rows = []
-
-    table_precursor_csv = os.path.join(outpath, 'table_precursor.csv')
-    blastn_csv = glob.glob(
-        os.path.join(
-            outpath,
-            'hivseqinr*',
-            'Results_Intermediate',
-            'Output_Blastn_HXB2MEGA28_tabdelim.txt'
-        )
-    )[0]
-
-    blastn_columns = ['qseqid',
-                      'qlen',
-                      'sseqid',
-                      'sgi',
-                      'slen',
-                      'qstart',
-                      'qend',
-                      'sstart',
-                      'send',
-                      'evalue',
-                      'bitscore',
-                      'length',
-                      'pident',
-                      'nident',
-                      'btop',
-                      'stitle',
-                      'sstrand']
-    with open(blastn_csv, 'r') as blastn_file:
-        blastn_reader = DictReader(blastn_file, fieldnames=blastn_columns, delimiter='\t')
-        for row in blastn_reader:
-            if row['qseqid'] in ['8E5LAV', 'HXB2']:
-                # skip the positive control rows
-                continue
-            ref_start = int(row['sstart'])
-            ref_end = int(row['send'])
-            if ref_end <= LEFT_PRIMER_END or ref_start >= RIGHT_PRIMER_START:
-                # skip unspecific matches of LTR at start and end
-                continue
-            [run_name, sample_name, _, _] = row['qseqid'].split('::')
-            is_inverted = ''
-            if ref_end < ref_start:
-                # automatically recognize inverted regions
-                new_end = ref_start
-                ref_start = ref_end
-                ref_end = new_end
-                is_inverted = 'yes'
-            landscape_entry = {'ref_start': ref_start,
-                               'ref_end': ref_end,
-                               'samp_name': sample_name,
-                               'run_name': run_name,
-                               'is_inverted': is_inverted,
-                               'is_defective': ''}
-            # is_defective is empty for now, will be filled manually
-            landscape_rows.append(landscape_entry)
-
-    with open(table_precursor_csv, 'r') as tab_prec:
-        tab_prec_reader = DictReader(tab_prec)
-        for row in tab_prec_reader:
-            samp_name = row['sample']
-            verdict = row['MyVerdict']
-            for entry in landscape_rows:
-                if entry['samp_name'] == samp_name:
-                    entry['defect'] = verdict
-
-    landscape_columns = ['samp_name', 'run_name', 'ref_start', 'ref_end', 'defect', 'is_inverted', 'is_defective']
-    with open(proviral_landscape_csv, 'w') as landscape_file:
-        landscape_writer = csv.DictWriter(landscape_file, fieldnames=landscape_columns)
-        landscape_writer.writeheader()
-        landscape_writer.writerows(landscape_rows)
-
-
 def get_softclipped_region(query, alignment, alignment_path):
     try:
-        size, op = alignment.iloc[0]['cigar'][0]
+        first_match = alignment[0]
     except IndexError:
         logger.warning('No alignment in %s!', alignment_path)
         return
+
+    cigar = first_match[5]
+    size, op = split_cigar(cigar)[0]
     if op != 'S':
         return
+
     size = int(size)
     return query[:size]
 
diff --git a/setup.py b/setup.py
index 069adcc..813dd68 100644
--- a/setup.py
+++ b/setup.py
@@ -8,8 +8,9 @@
         'gotoh @ git+https://github.com/cfe-lab/MiCall.git@v7.7.0#egg=gotoh&subdirectory=micall/alignment',
         'numpy==1.25.1',
         'python-Levenshtein==0.12.0',
-        'pandas==2.0.2',
+        'pandas==2.2.2',
         'requests==2.31.0',
+        'cfeintact @ git+https://github.com/cfe-lab/CFEIntact.git@v1.23.0',
         'pyyaml'
     ],
     package_data={
diff --git a/tests/test_utils/test_utils.py b/tests/test_utils/test_utils.py
index d378d2c..28d0adc 100644
--- a/tests/test_utils/test_utils.py
+++ b/tests/test_utils/test_utils.py
@@ -16,7 +16,8 @@ def test_get_softclip_start():
     # Normally this alignment would be generated by a separate function
     aln_path = example / 'alignment.sam'
     aln = utils.load_samfile(aln_path)
-    size, op = aln.iloc[0]['cigar'][0]
+    cigar = aln[0][5]
+    size, op = utils.split_cigar(cigar)[0]
     size = int(size)
     query_fasta = Fasta(example / 'query.fasta')
     query_sequence = None
@@ -110,4 +111,4 @@ def test_getSamplesFromCascade():
     samples = utils.get_samples_from_cascade(cascade)
     assert len(samples) == 10
     for i in range(10):
-        assert samples[str(i)] == i
\ No newline at end of file
+        assert samples[str(i)] == i