Do what matters.
Describe your work — wovana delivers.
›Bring your own model provider — a cloud account you already pay for, or a local model you run. Multi-provider by design, no lock-in, and your keys never leave your machine.
Some work is too variable for rule-based automation — and too important for a single prompt.
It's the recurring, high-stakes work your experts still do by hand — a contract reviewed three times, an RFP assembled across a dozen emails, a claim validated, routed, and posted step by step. Each step takes judgment, and each needs a check before the next. That's the work wovana is built for.
Describe it. Shape it. Watch it run.
You author pipelines on a canvas — no code, no glue scripts. The platform compiles what you build into a runnable, quality-gated workflow you can launch, watch, and improve.
Drag stages onto the canvas yourself — or describe the goal and wovana drafts the first pipeline for you to edit.
Tune each typed stage — checks, revision loop, model. A cheap model to validate, a strong one for the decisions that matter.
Fully autonomous, or with human checkpoints for the calls that need a person. Watch live — pauses on a checkpoint, resumes across restarts.
Compare revisions on real outcome data — or let wovana read the results and tune the workflow. Promote the winner. No code, ever.
An output is done when it passes its checks — not when a model stops typing.
Quality loops run between stages. Incomplete, contradictory, or off-policy output is routed back for revision before the work moves on — and every gate decision is logged and inspectable.
Semantic review, on by default
A reviewer judges substance, not just format — flagging placeholder, ambiguous, or contradictory content and policy gaps. Document Quality and Process Compliance run by default; data-consistency and deeper compliance review are one switch away.
Loud, never quiet
A loop converges or escalates out loud — it never declares a silent success on an unresolved blocker, and never spins forever. A raised blocker closes through a real fix or a recorded deferral.
No inherited mistakes
A blind-review stage deliberately withholds prior reasoning, so a reviewer can't be biased by — or inherit — an earlier stage's mistake. It checks the work, not the story told about it.
Where raw AI hallucinates, wovana catches it.
We wanted to prove that on a real, consequential problem — publicly, against ground truth anyone can check. So we ran wovana against the most infamous AI-in-the-wild failure: the Mata v. Avianca brief, where attorneys filed six ChatGPT-fabricated citations and were sanctioned $5,000. The court's own sanctions opinion was the answer key.
wovana adjudicated all 19 citations — flagging every fabricated and mis-cited authority, and passing only the two that were legitimate. No fabrication slipped through; no real authority was failed.
A proof of concept built on free, public legal databases (CourtListener, the Caselaw Access Project, Cornell LII). Validated in a completed run — not a promise about every run. The two review-flagged citations were routed to a human rather than auto-failed. It does not replace Westlaw KeyCite or LexisNexis Shepard's for comprehensive negative-treatment analysis.
Teams also build RFP responses, contract analysis, document intake, and fundraising and outreach workflows on wovana. wovana is the surface you build them on — not a catalog of pre-packaged ones.
Your documents never leave your machine.
- ✓Bring your own provider. You supply your own model access — a paid cloud account or a local model you run. wovana drives it and reads no keys.
- ✓Documents stay local. The control plane holds only your pipeline definitions and run state. Your documents and model calls stay on your machine and never cross the wire.
- ✓Credentials by name only. Secrets are referenced by name and resolved locally — they never appear in logs, metadata, or stored artifacts.
- ✓A real audit trail. Every run is versioned and content-addressed: snapshotted inputs, per-stage outputs with lineage, an append-only event stream, and immutable attempt history — verifiable offline.
- ✓Closed by default. Deployment profiles refuse public binds, and per-stage telemetry records model, reasoning, duration, and token counts — never cost.
The no-code path has a deep end.
Everything above is authored without code. When you need exactness or an integration, the same pipeline reaches further — the depth is there when you want it, never in your way when you don't.
Bind an exact action
Make a stage run an exact command, an HTTP call, or a nested sub-workflow instead of a model. Deterministic and AI stages share the same quality loops and routing.
Drive it from your stack
Resolve a contract, launch with an idempotency key (single or batch), and subscribe to a signed webhook. A built-in MCP server exposes the same controls to your own agents.
Connect any system
Write one small function and the SDK turns it into a pipeline step — managing the full credential lifecycle and keeping secrets off the wire. A Google Drive connector ships for workflow import and export.
Design the workflow. wovana does the work — better than a model alone.
wovana is in private beta. Request early access and we'll reach out as we open the door.
Expert work. AI without the code.