Open source stack for private AI
Curated projects we track for self-hosted inference, knowledge systems, agent learning, safety, and edge deployment. External links; verify licenses and fit for your environment.
Self-hosted & embedded AI
Run models on your hardware without cloud dependency.
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Odysseus
Self-hosted AI stack for local inference and private assistant workflows.
Why we track it: closest open analog to Sovra's own sovereign-core runtime — useful reference point for local inference architecture.
OCR
Document and image text extraction for on-prem pipelines.
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Unlimited OCR (Baidu)
Open OCR tooling for high-volume text recognition from images and scans.
Why we track it: feeds the document-ingestion side of an on-device RAG pipeline — scanned manuals and photographed documents, processed without leaving the device.
Agent RL & live learning
Reinforcement and online learning bridges for LLM agents.
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AReaL
RL bridge for LLM agents — connect training loops to real agent runtimes.
Why we track it: relevant to command-execution agents that should improve from real on-device usage rather than only static fine-tuning.
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ODS (Osmantic)
Osmantic data system for agent-oriented storage and operational learning flows.
Why we track it: pairs with agent RL to store the operational/episodic data an on-device agent accumulates over time.
Knowledge base & data
Metadata, catalogs, and retrieval beyond vanilla RAG.
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DataHub
Metadata platform for data discovery, lineage, and governed knowledge bases.
Why we track it: the governance layer teams need once they're running Sovra across a fleet of devices and want to track what data feeds which deployment.
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PixelRAG
Pixel-oriented retrieval approach aimed at richer grounding than classic chunk RAG.
Why we track it: a benchmark candidate against Sovra's default chunk-based RAG for image-heavy technical documents.
Security & LLM safety
Red teaming, guardrails, and structured policy via MCP.
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DeepTeam (Confident AI)
LLM red-teaming framework for adversarial testing and vulnerability discovery.
Why we track it: the kind of adversarial testing a command-execution layer needs before it's trusted to trigger real actions.
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Ontology MCP Server
MCP server exposing ontologies so agents can reason over typed domain concepts.
Why we track it: a pattern for exposing structured domain knowledge (not just plain-text chunks) to a validated command layer via MCP.
Healthcare AI
Open research and tooling from Google Health.
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Google Health (open source)
Organization hub for health-related open-source models, datasets, and tools.
Why we track it: a reference point for domain-specific model and dataset work when Sovra hardware is deployed in clinical or health-adjacent settings.
Meeting & local transcription
Privacy-first capture without sending audio to the cloud.
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Meetily
Local meeting AI built in Rust with Ollama — transcription and summaries on-device.
Why we track it: applies the same no-cloud principle Sovra uses for assistant flows to real-time transcription — good template for a fully local meeting-notes add-on.
Knowledge extraction
Structure text into graphs for downstream retrieval and reasoning.
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Hyper-Extract
Hypergraph extraction from unstructured text for richer knowledge representation.
Why we track it: turns ingested documents into a graph instead of flat chunks — potential fidelity upgrade for the knowledge-base tier's RAG.
Local dev & infrastructure
Emulate cloud services on your laptop for private AI CI and testing.
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floci
Lightweight local emulator alternative to AWS-style services for dev and integration tests.
Why we track it: lets teams building on Sovra emulate cloud services locally during dev/CI instead of needing live cloud accounts for integration tests.
Building on private hardware?
Map these tools to your edge or on-prem stack with our hardware configurator and Sovra tiers.