{"adoption": {"forks": 203, "observed_at": "2026-08-28T04:04:45.165266+00:00", "stars": 1445}, "canonical_url": "https://ross.abutalabs.com/products/concrete-ml", "card": {"archived": false, "artifact_type": "library", "description": "Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks.", "domain": ["machine-learning", "privacy", "data-science", "security"], "enriched": true, "function": ["machine-learning", "cryptography", "privacy", "security"], "health_score": 90, "homepage": null, "language": "Python", "license": "NOASSERTION", "license_family": "other", "maturity": "active", "member_repos": ["zama-ai/concrete-ml"], "name": "zama-ai/concrete-ml", "platform": ["python"], "pushed_at": "2026-08-04T11:50:16+00:00", "repo": "zama-ai/concrete-ml", "stars": 1445, "tags": ["fhe", "fully-homomorphic-encryption", "ppml", "scikit-learn", "pytorch", "encrypted-inference", "privacy-preserving-ml"], "topics": ["python", "data-science", "privacy", "torch", "scikit-learn", "homomorphic-encryption", "machine-learning", "fhe", "tfhe", "ppml", "fully-homomorphic-encryption"], "urls": [], "use_cases": ["run machine learning inference on encrypted data", "train models without exposing sensitive training data", "analyze healthcare data while preserving patient privacy", "convert scikit-learn models to FHE equivalents", "deploy PyTorch models that operate on encrypted inputs", "build privacy-compliant ML services under strict data regulations"], "what_it_is": "Concrete ML is a privacy-preserving machine learning library built on top of Zama's Concrete FHE compiler. It lets data scientists convert scikit-learn-style models and PyTorch neural networks into fully homomorphic encryption equivalents for inference or training on encrypted data without cryptography expertise.", "when_to_avoid": ["you need low-latency inference, as FHE adds large overhead", "your models rely on operations unsupported by FHE quantization", "you only need standard ML without privacy constraints", "you need a non-Python stack"], "when_to_choose": ["you need ML on encrypted data without decrypting it", "your models use scikit-learn, XGBoost, or PyTorch APIs", "data privacy regulations prevent plaintext processing", "you want FHE without writing cryptography code"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/concrete-ml", "repo": "zama-ai/concrete-ml", "role": "main", "score": 69}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:04:45.165266+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T04:36:15.857050+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "2922506b8169296e58e1b679a2d22c22af7800e43c70bb001d2a571ac0b809d0", "fetched_at": "2026-08-28T04:04:45.165266+00:00", "kind": "readme", "missing": false, "url": "https://github.com/zama-ai/concrete-ml"}, {"content_hash": "d775e8594b69b40ce49e3e2982d7f453d1b2f909deab63bf4f96986a45a92c41", "fetched_at": "2026-08-29T11:46:13.375870+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/concrete-ml/json"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 96, "longevity": 100, "rhythm": 16}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 1624, "days_push": 29, "days_rel": 510, "gap_med": 95.5, "n_releases_24m": 3}, "score": 69, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}