Packages

Comprehensive benchmarking framework for AI research. Measures latency, throughput, cost, and reliability with percentile analysis and Nx numerical computations.

Model evaluation harness for standardized benchmarking with semantic similarity, exact match, and custom metrics.

Execution Plane process launch, stdio, PTY, and process-session runtime.

Execution Plane JSON-RPC framing and correlation lane.

Production adapters and pipelines for PortfolioCore. Vector stores, graph stores, embedders, Broadway pipelines, and advanced RAG strategies.

Hexagonal architecture core for building flexible RAG systems in Elixir.

Explainable AI (XAI) tools for the Crucible framework. Includes LIME implementations, SHAP-like explanations, feature attribution, and model interpretability for local and global explanations.

The definitive CI/CD platform for AI Quality.

Multi-model ensemble prediction with voting strategies for AI reliability. Leverages BEAM parallelism for massively concurrent LLM queries.

Experimental research framework for running AI benchmarks at scale. Provides orchestration, streaming processing with Flow/GenStage, and statistical analysis.

Adversarial testing and robustness framework for AI models with 25 attacks (character/word/semantic perturbations, prompt injection, jailbreak, extraction, inversion), defenses (detection/filtering/sanitization), certified robustness metrics, and attack composition.

Synapse integration for altar_ai - SDK-backed LLM providers for multi-agent workflows. Provides unified adapter layer for Gemini, Claude, and Codex with automatic fallback, workflow actions, signal handlers, and telemetry bridging.

A library to make building performant RAG systems in Elixir easy

Request hedging for tail latency reduction in distributed systems. Implements Google's 'Tail at Scale' with adaptive strategies. Reduces P99 latency by 75-96%.

A 100% faithful port of the DuckDB Python client to Elixir, using the DuckDB CLI for full API compatibility with the official Python client.

Configuration management with CLI parsing for Elixir

Structured causal reasoning chain logging for LLMs. Captures decision-making processes with cryptographic verification for transparency and debugging.

Advanced telemetry collection and analysis for AI research

Model versioning, artifact storage, and lineage tracking for ML pipelines

Production-ready data validation and quality library for Elixir ML pipelines. Provides 22 built-in expectations, drift detection, advanced profiling with outliers and correlations, statistical analysis, and comprehensive quality metrics for machine learning workflows.