Trustworthy AI,
Confident Decisions.
Ravel gates AI responses built on stale or low-confidence retrievals — and records every decision to an auditable trust ledger. Your teams see the system's real state, and act on answers they can defend.
Built for enterprise AI teams. No spam — early access invites only.
SLA for P1 incidents?
passed · conf 94%
Q3 revenue by segment?
passed · conf 88%
EU data residency policy?
gated · conf 34%
Refund window for annual plan?
passed · conf 91%
Built for the AI teams behind critical operations
Most RAG systems never tell you when to doubt them
A retrieval can be stale, thin, or off-topic — and the model will still answer with total confidence. Ravel inserts a gate between retrieval and generation, then records the decision.
Retrieve & score
As context is retrieved, Ravel scores its confidence and freshness for the specific question being asked.
Gate the response
Above threshold, the grounded answer passes with a citation. Below it, the response is gated and the state goes degraded.
Write to the ledger
The query, sources, score, and outcome are recorded as an immutable entry — ready for audit and compliance review.
Watch the trust gate make a real decision
Pick a scenario or write your own. Ravel scores the retrieval and either returns a grounded, cited answer — or gates it and tells you why.
Run the gate to see a real confidence-scored decision and its ledger entry.
Everything you need to trust — and prove — your AI
Confidence gating
Score every retrieval before generation. Responses built on stale or low-confidence context are gated — never dressed up as a confident hallucination.
Auditable trust ledger
Each decision is written as an immutable, timestamped entry — query, sources, score, gate outcome. A defensible record of why the AI answered, or didn't.
Operational state signals
Surface operational vs degraded state to your users and systems in real time, so people make informed decisions about the AI output in front of them.
Compliance-grade trail
Retention, redaction, and export controls designed for regulated review. Give audit and risk teams the evidence they ask for — without spelunking logs.
Staleness detection
Freshness-aware scoring flags retrievals grounded in outdated sources, catching the silent drift that offline eval suites miss in production.
Drop-in for your RAG
Sits between retrieval and generation with a thin integration. Keep your model, your vector store, your stack — add the trust layer on top.
An auditable trust ledger for every RAG output
Confidence gating is where Ravel starts. Where it wins is the ledger: a defensible, immutable record of what your AI was asked, what it retrieved, how confident it was, and whether it was allowed to answer.
- Immutable, timestamped entries for every decision
- Query, sources, confidence score, and gate outcome captured together
- Retention, redaction, and export built for regulated review
- Turn “the AI said so” into evidence your auditors accept
- timestamp
- 2026-08-01T09:41:22Z
- query
- “EU data residency policy?”
- sources
- kb/policy_v2.md · kb/legal_faq.md
- freshness
- stale (last updated 24mo ago)
- confidence
- 34%
- decision
- GATED
- state
- degraded
We fill the gaps others leave open
Evaluation suites and content guardrails are valuable. Ravel owns the real-time trust gate and the audit ledger they don't.
| Capability |  Ravel | Galileo | Arize AI | Bedrock Guardrails |
|---|---|---|---|---|
| Real-time confidence gating on retrieval | ||||
| Immutable, timestamped audit ledger | ||||
| Staleness / freshness-aware scoring | ||||
| User-facing operational state | ||||
| Compliance & export for regulated review | ||||
| Offline evaluation & dashboards |
Comparison reflects Ravel's product positioning. Named products are trademarks of their respective owners.
99.95%
Target platform uptime
<15 min
P1 first response
100%
Decisions logged to the ledger
Every RAG call
Confidence-scored inline
Trusted where a wrong answer is expensive
Ravel turned “the model sounded sure” into an actual number our risk committee trusts. The audit ledger is what got us over the compliance line.
Gating on stale retrievals cut our worst hallucinations to near zero. Support now shows an operational state instead of a confident wrong answer.
We evaluated the usual suspects. Ravel was the only one that owned the audit layer end-to-end instead of leaving it to us.
Illustrative testimonials shown with fictional names for demonstration purposes.
A platform fee that scales with trust
Per-account pricing for mid-market enterprise AI teams. Tiers scale with monitored volume and the depth of audit & compliance you need.
Team
For a first production RAG workload.
- Confidence gating on one workload
- Trust ledger with 90-day retention
- Operational state signals
- Email support
Enterprise
Usage-tiered platform fee for critical AI operations.
- Unlimited gated workloads
- Immutable ledger with custom retention
- Compliance export & redaction controls
- SSO, roles & audit access
- <15 min P1 support, 99.95% uptime
Regulated
For teams under formal audit obligations.
- Everything in Enterprise
- Tamper-evident hash-chained ledger
- Dedicated compliance onboarding
- Data-residency & deployment options
Scaling from a focused launch cohort to 130+ enterprise accounts — priced on the audit & compliance value we deliver, not seats.
Questions, answered
Every RAG response Ravel evaluates is recorded as an immutable, timestamped entry: the query, the retrieved sources, the confidence score, the gate decision, and the operational state at that moment. It becomes your auditable record of why the AI answered — or chose not to — for compliance and post-incident review.
Guardrails filter obviously unsafe content. Ravel goes upstream: it inspects retrieval quality and freshness before generation, then gates responses that rest on stale or low-confidence context. Instead of a confident-sounding hallucination, your users get a clear operational state.
Those tools are excellent at offline evaluation, observability dashboards, and content-level guardrails. Ravel owns the layer they leave open: a real-time gate on retrieval confidence paired with a compliance-grade audit ledger that stands up to enterprise review.
Confidence scoring runs inline with retrieval and adds low double-digit milliseconds in typical deployments. Gating decisions and ledger writes are asynchronous where possible, so your happy path stays fast.
Ravel scores retrieval confidence and records metadata for the audit ledger. You control retention and redaction, and it can be deployed to keep sensitive payloads inside your own environment. Full data-handling detail is shared during enterprise onboarding.
Ravel is a per-account platform fee priced for mid-market enterprise. Tiers scale with monitored volume and the depth of audit/compliance features you need. Talk to us and we'll map a tier to your team.
Ship AI your auditors can trust
Join the waitlist for early enterprise access. Bring your RAG stack — leave with a trust layer and an audit trail.
Prefer to talk? See enterprise plans.