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Semantica: Graph-Native Infrastructure for Context and Accountable AI Systems. It is listed under Data & Analytics on AI Registry as a free tool.
The tools below are approved listings in the same category, ordered by how closely their tags match Semantica. This is an automatic list. We have not written a researched verdict for Semantica yet, so treat it as a shortlist and check each vendor's pricing page before switching.
Built from each tool's listing. Vendors can update their own listing after claiming it.
Interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible).
imodels is an open source Python package for concise, transparent and accurate predictive modeling. It gives data scientists a scikit learn compatible interface to interpretable models, so a classifier or regressor can be imported, fitted and used with the familiar fit and predict methods. The aim is to replace black b...
The open source AI engineering platform for agents, LLMs, and ML models.
MLflow is an open source platform for building, debugging, evaluating and monitoring LLM applications, agents and traditional machine learning models. It is backed by the Linux Foundation and is used by developers, data scientists and ML platform teams, with support for Python, TypeScript and JavaScript, Java and R and...
PageIndex: Document Index for Vectorless, Reasoning-based RAG
PageIndex is a document question answering engine that retrieves information by reasoning over a document's structure rather than by vector similarity search. The vendor describes it as a vectorless, reasoning based retrieval system that mirrors how a person reads a long document, and it cites 98.7 percent accuracy on ...
Postgres with GPUs for ML/AI apps.
PostgresML is a Postgres database with GPUs attached for machine learning and AI applications. It keeps vectors, models and application data in one place, so a team can create embeddings, index, filter and rank vectors, and run inference and grounded answers directly in SQL instead of operating a separate vector databa...
Multi-class confusion matrix library in Python
PyCM is a multi class confusion matrix library written in Python. It is used to evaluate classification models after training, accepting either input data vectors or a ready made matrix and then computing a broad set of per class and overall statistics from it. The project describes itself as the swiss army knife of co...
A refreshing functional take on deep learning, compatible with your favorite libraries
Thinc is a lightweight, type checked deep learning library for composing models in Python. It comes from the makers of spaCy and Prodigy, and earlier versions of the library have powered spaCy since its release. The current design is a redesign that takes a functional approach to defining neural networks. The library ...