For teams shipping under audit
Signed evidence on every AI-generated artifact, mapped to your standard. IEC 62304 · IEC 62443 · DO-178C · NIST · ISO 27001.
Built for teams shipping under audit
Compliance leads need evidence. Engineers need not to ship LLM slop. Pick your entry point.
“My team uses LLMs to write code under IEC 62304. The auditor wants traceability. I want to sleep at night.”
“I want my LLM-assisted code reviewed by something stricter than another LLM.”
Path A — Compliance
Generic AI tools tell you the LLM ran. We tell you whether what it produced will survive an audit.
LLM says “requirement covered”. Validator says: 12/12 text-match, 0/12 structural. We expose the gap before the auditor does.
No cryptographic trace from requirement to spec to code to test. We sign each link with BLAKE3 and Ed25519 — tamper-evident, verifiable offline.
IEC 62304 §5.5 today. §5.5.x sub-clauses tomorrow. Our standards plugins are versioned and shipped as data, not as code rewrites.
Path B — Engineering
Friction detection, design-before-code, and a HUD that lets you reject any step before it lands.
Auth gaps, hardcoded secrets, AST-level smells. 8 languages: Python, Rust, JS/TS, Go, Java, C#, C/C++, Ada.
Design before code. Adversarial critique catches ambiguity before a single line is generated.
TalaSala TUI + VS Code + Desktop. Approve or reject every step. Bring your own LLM, local or cloud.
$ pip install jagora && jagora design workflow my-app/
TalaSala is where every step gets approved, rejected, signed, timestamped, and mapped to clauses — in real time. The artifact you ship is the artifact the auditor reviews.
Ratatui + Axum API. 4 views. SSH-friendly, air-gap ready.
Electrobun + React. Native feel on macOS, Windows, Linux.
Dashboard, feature tracker, run page. In-editor pilot.
Rust core, local services, your LLM. No phone-home, no SaaS lock-in.
BLAKE3 hashing and Ed25519 signatures on every audit record. Verifiable offline, no Jagora server in the loop.
PostgreSQL for state, Qdrant for vectors, Redis for queues. The exact same stack on your laptop and in CI.
Every design decision, code generation step, and git push is signed before it runs. The evidence is the artifact.
Four trust tiers — from bwrap to Firecracker (the AWS Lambda sandbox) — plus eBPF egress filtering. Apache 2.0.
Activity log and document RAG, with vector and graph indexes. Stays on your machine. Wipeable per project.
OpenAI, Anthropic, Mistral, Google, xAI, DeepSeek, Meta, plus any OpenAI-compatible endpoint. Or fully local via Ollama or vLLM.
What changes is who runs it, where it runs, and what gets signed.
Self-serve
Run the validators on one repo
Team
Adopt it across your engineers
/month per seat
Audit-ready
Add the signed evidence chain
/month per seat
On-premise
Air-gapped, your standard, your perimeter
contact us
Four tools that ship with Jagora. Each one Apache-2.0, usable on its own.
The Sandbox
4-tier trust isolation (bwrap, unshare, gVisor, Firecracker) with eBPF egress enforcement. Apache 2.0 open source.
pip install zelo
The Evidence Engine
BLAKE3-signed, chain-linked audit trails. Tamper-evident logs for every AI action.
cargo install ushahidi
The Egress Judge
Sign your agent's egress intent at build time. Judge every outbound call at runtime. In-process Rust crate.
cargo add oluso-core
The Graph Layer
Code as a typed graph across 10 languages. Tree-sitter parsing plus use-def chains, call edges, regex literals.
cargo add codemap-core
Engineers
$ pip install jagora
Run the validators on your repo this afternoon.
Compliance leads
→ Book a 30-min POCWe run them on one of your audit-bound projects and send you the signed report.
No demo theater. No sales call. The artifacts speak.