AI Agent

Tessera

An open, deterministic evidence layer for enterprise AI agents that grounds every claim in traceable source records and gates actions behind approval.

What is Tessera?

Tessera is an open-source framework that ingests heterogeneous enterprise data, resolves entities into a knowledge graph, and answers questions through a grounded conversational interface where every claim is traced back to its source evidence, with a faithfulness metric to measure trust.

Tessera vs Similar AI Tools

Pricing ModelFreeFree, FreemiumFreeFree
Free Credits
Key Features
  • Universal ingestion of structured and unstructured data
  • Cross-source entity resolution into a unified knowledge graph
  • Grounded conversational reasoning with per-claim provenance
  • Multi-agent workflow with verification and self-healing
  • 50+ AI models auto-routed per agent
  • 1000+ OAuth2 app integrations
  • Seven breakable boxes covering OWASP Agentic Top-10 vulnerabilities
  • Three guided simulations for cascading failures, human-agent trust, and rogue agents
  • Network-isolated Docker containers for safe execution
  • Code-to-runtime reasoning across cloud, Git, and Kubernetes
  • Action-gate enforces read-only policy on every API call
  • Sandboxed JavaScript execution for concurrent research
Pros
  • All claims are traceable to exact source records
  • Deterministic and can run on-prem without any model vendor
  • Replaces 10+ separate tools with one platform
  • Multi-agent orchestration saves time and context switching
  • Covers full OWASP Agentic Top-10 in a realistic manner
  • Docker isolation prevents accidental damage
  • Read-only by construction prevents accidental writes
  • Evidence-backed verification cross-checks every finding
Cons
  • Currently synthetic demo data; real data requires connector setup
  • Entity resolution has tunable thresholds and known limitations
  • Free tier limited to 5,000 credits per month
  • May have a learning curve for complex workflows
  • Requires Docker and technical setup
  • Not for production use; only for lab environments
  • Requires an LLM API key, incurring token costs
  • Limited to read-only operations, cannot remediate
Best For
  • Enterprise teams building trustworthy AI agents
  • Developers needing auditable AI for internal tools
  • Marketing teams
  • Content creators
  • Security researchers focusing on AI agent vulnerabilities
  • Developers building MCP-based applications
  • Security engineers
  • DevOps teams

How to use Tessera?

  1. 1Clone the repo and run `uv sync` to set up the environment.
  2. 2Use the CLI: `uv run tessera` to ask grounded questions, or `uv run tessera-ui` for the web interface.
  3. 3Connect your data via `uv run tessera connect github <owner/repo>` or by declaring a `tessera.toml` config.
  4. 4Run the evaluation harness with `uv run tessera-eval` to measure faithfulness.

Tessera Key Features

  • Universal ingestion of structured and unstructured data
  • Cross-source entity resolution into a unified knowledge graph
  • Grounded conversational reasoning with per-claim provenance
  • Quantified trust via a faithfulness metric in CI
  • Evidence-gated actions over MCP with proposal, preview, and approval
  • Deterministic retrieval and reasoning (no LLM in trust path)
  • Two reference verticals: Business Data Copilot and DevEx Copilot

Tessera Use Cases

  • Enterprise AI agents requiring auditable, grounded answers
  • Root-cause analysis of CI/CD pipeline failures with traced evidence
  • Business data copilot across databases, documents, and logs
  • Compliance-sensitive environments that need on-prem, deterministic AI

Tessera Pricing & Free Credits

Tessera currently operates on a Free model.

This tool is completely free to use

Open Source

Free

MIT-licensed code; free to use, modify, and deploy

Tessera Pros & Cons

Pros

  • All claims are traceable to exact source records
  • Deterministic and can run on-prem without any model vendor
  • Built-in faithfulness metric that can fail in CI
  • Supports both structured and unstructured data
  • MCP-native with propose-approve-execute workflow

Cons

  • Currently synthetic demo data; real data requires connector setup
  • Entity resolution has tunable thresholds and known limitations
  • Requires Python and UV toolchain; not a plug-and-play SaaS

What is Tessera best for?

  • Enterprise teams building trustworthy AI agents
  • Developers needing auditable AI for internal tools
  • SAP-centric environments (runs on SAP AI Core / HANA Cloud)
  • Teams that want to measure AI faithfulness with CI gates

Tessera FAQ

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