An AI that shows its work
"Can I trust what the AI tells me — and can I prove what it delivered?" is the question every CS leader now has to answer. Velsano is built to answer it: every output graded against your data, autonomy earned from real results, and one governed path for every model call. No black box, and no invented accuracy stats.
Every AI output is graded — and you can see the grade
- Grounded, not guessed — Each risk narrative and account brief is scored on whether its evidence is actually backed by your data — cited sources must trace to real signals, or the output is flagged. Ungrounded claims are caught, not shipped.
- A frozen regression suite — A locked 'golden' corpus runs on every build. If a change would let an agent hallucinate evidence, drift from the live signals, or contradict its own score, the build fails — before it ever reaches you.
- Quality on your screen, not in a lab — The AI Insights page shows the live output-quality score, the clean rate, and the lowest-scoring recent outputs — so you audit the AI the same way you audit a CSM.
Autonomy is earned, not assumed
- Propose first, always — Out of the box, agents propose work into an inbox and a human approves it. Nothing reaches a customer without a person deciding it should.
- Trust is scored per agent — Each agent earns a trust tier per action from its real track record — approvals, rejections, and downstream outcomes. Only an agent that has genuinely earned it can ever act touch-free, and negative outcomes demote it.
- Guardrails that fail closed — Even an earned-autonomous agent is health-gated, topic-allowlisted, send-capped, and quiet-hours aware — and any ambiguity resolves to "ask a human," never "send anyway."
The AI is accountable for outcomes
- Every action is reconciled — We don't stop at 'the AI suggested it.' Each action is tied back to what actually happened next — did the renewal close, did health recover — and that record feeds the trust score.
- Attribution you can defend — The effectiveness view shows how many retained renewals had a prior AI action, so you can state the AI's contribution to leadership without hand-waving.
- A value ledger, not a vanity metric — Promised value is captured against realized value over time, as an immutable record — the evidence pack a CSM brings to a QBR, and the answer to "what did this actually deliver?"
Governed, metered, and injection-aware
- One gateway, no shadow calls — All LLM traffic flows through a single governed gateway to Anthropic, with per-workspace usage metering, spend caps, and kill switches. Embeddings (off by default) flow through one gateway to OpenAI. Nothing else calls a model.
- You decide what AI can see — Admins can deny specific AI tools and data objects per workspace — and the denylist applies everywhere the AI runs: copilot, agents, and the external MCP server alike.
- Hostile content stays data — Untrusted customer text — emails, transcripts, tickets — is fenced and sanitized before it reaches a prompt, so a malicious message can't hijack the AI.
Honesty is the product
We don't publish accuracy numbers we can't stand behind, or claim certifications we don't hold. What we do publish — the grading, the earned-autonomy model, the outcome reconciliation — is real, shipped, and running on every workspace. That's the bar we hold our AI to, and the one you should hold every vendor's to.