01 / The governed AI layer

Your AI can sound right.
Pinavia makes it
provable.

Pinavia turns institutional evidence into governed AI workflows for boards, regulated teams, diligence teams, and consulting firms. Ask a question, see the sources, draft the decision, and keep the approval trail intact.

Start pilot Run the diagnostic Enter NexusAI

The same context is re-built every time.

Documents, emails, board packs, deal rooms, and policies keep being re-uploaded or re-explained before useful work can start.

The answer sounds complete before it is safe.

A fluent response can still miss a jurisdiction, an approval boundary, a caveat, or the source a regulator will ask to see.

The decision trail appears after the decision.

Teams approve in chat, email, and meetings, then try to reconstruct evidence, ownership, and rationale when scrutiny arrives.

Live product pattern

A single question becomes a governed path

Evidence-first

User question

What changes if we approve market expansion while the compliance file is incomplete?

Ordinary AI

plausible

A confident answer, but no operating proof.

Source base is unclear.
Jurisdiction and approval limits are inferred.
No owner is forced before action.

Pinavia

AI drafted

A sourced answer with the next human step attached.

Regulation, board pack, and risk register cited.
Gaps and caveats shown before recommendation.
Decision draft routed to the named approver.

Jurisdiction

Assumed from the question

SBP EMI scope flagged before answer

Evidence

Generic summary

Board pack, policy, and regulation cited

Action

Advice in chat

Draft decision routed for approval

Boundary

May imply approval

Human owner required before action

02 / Where the money goes

Generic AI spend leaks before it becomes governed value.

The diagnostic turns this from a generic chart into your actual workflow map. Until then, this animation shows the pattern we expect to test: money disappears into context rebuild, rework, and after-the-fact approval reconstruction unless the workflow is designed around evidence, owners, and proof.

Start pilot

Before governance

$100

Context rebuilt$42

Unverified rework$24

Approval trail rebuilt$18

Disconnected routing$10

Reusable proof$6

Evidence

Ask

Caveat

Owner

Proof

Animated proof loop

Source memory feeds the answer, the answer exposes caveats, the owner approves, and the proof artifact survives the meeting.

With Pinavia

$100

Evidence memory$32

Verification$24

Human approval path$22

Audit-ready proof$14

Model run cost$8

Illustrative allocation only. Real values should come from the diagnostic using your workflow, evidence estate, approval model, and deployment costs.

03 / How a decision earns its proof

Most AI gives you an answer. Pinavia gives you a passport.

A regulated decision is not the sentence the model produced. It is that sentence plus its sources, its caveats, the person who owned it, the gate it passed, and the trail that proves it. Watch one question earn all seven.

The decision passport

One question. Seven checks. Portable proof.

The animation shows the proof object being assembled, not just the answer being generated. Each checkpoint adds authority before the export can leave.

Assembly progress14%

Decision passport

PSP-2026-0714

1/7In progress

Sources: 6 documents · board pack, SBP EMI Regs 2019 Reg 5, onboarding SOP v4
Draft finding: pending
Confidence: pending
Owner: pending
Approval: pending
Audit: pending
Passport: pending

Every row is written once and travels with the decision. Remove any one of them and the export is refused.

Current proof object

Evidence bundle

Source base locked

Evidence

Authority

Export

Evidence

Retrieved from the workspace. Nothing external, nothing invented.

04 / The operating layer

Add evidence once. Use it everywhere decisions happen.

Pinavia sits between your institutional knowledge and the models your teams already want to use. It keeps source memory, checks claims, and routes consequential work to humans.

Inputs

Board packs

Policies

Deal rooms

Regulations

Email evidence

Pinavia governed core

Evidence memory

one source base

Pinavia remembers approved sources as structured operating context, so teams ask from the same evidence base instead of starting over.

Verification

source trace

Claims are checked against visible sources before the output is treated as decision support.

Human routing

named owner

Drafts move to the right owner, committee, or approval queue without pretending the machine has authority.

Outputs

Sourced answers

Decision drafts

Approval queues

Audit trails

Client-ready packs

05 / Why it holds up

An answer you can prove you were right to approve.

100%

of governed answers carry source references or refuse when the source base is not strong enough.

Product guarantee

consequential actions leave the system without a named, identity-bound human approval step.

Governance boundary

regulated rooms run on one shared core for ingestion, evidence, agents, billing, and controls.

Product family

06 / What is uniquely Pinavia

Built for the moment after an AI answer sounds convincing.

Pinavia is not trying to be the loudest model interface. Its job is to make high-stakes AI work legible, sourced, bounded, and safe enough for regulated teams to use in front of boards, committees, clients, and regulators.

Human approval is a product primitive

approval boundary

The machine can draft, route, summarize, and compare. It cannot approve, sign, file, certify, or mark a matter complete.

That boundary is designed into the workflow, not hidden in a policy note. Every consequential output lands with an owner, a status, and an approval path.

Evidence is visible before the answer becomes useful

source-first UI

Sources, caveats, confidence, and missing-evidence warnings sit beside the answer rather than behind a separate audit export.

A buyer can see what the system relied on before they turn an answer into a decision, minutes note, filing pack, or investment memo.

Each vertical owns its own workflow

domain registry

Quorum, Meridian, Vantage, and Nucleus are not skins over one generic chatbot arc.

Board governance, regulatory filings, diligence, and consulting delivery each use their own objects, stages, refusal rules, and user inputs.

Regulated work is designed around what AI must not do

refusal logic

The product describes no-go zones as clearly as capabilities.

For Meridian that means no automatic filing or certification. For Vantage, no autonomous investable/rejected decision. For Quorum, no silent approval of board actions.

One governed core, many product P&Ls

shared engine

Ingestion, governance, evidence, agent controls, and billing are shared. Buyer-facing workflows stay separate.

This lets Pinavia sell credible vertical products without rebuilding the infrastructure layer each time or forcing every buyer into the same vocabulary.

White-label governance for advisory firms

partner-ready

Nucleus is designed for partners that need their own methodology and brand on top of Pinavia controls.

Logos, accents, and templates can flex; status colours, trust patterns, human approval, and consequence previews stay contractually fixed.

07 / Why Pinavia is different

Context memory is necessary. Governed action is the product.

A context-memory company helps AI remember, retrieve, verify, and route knowledge more efficiently. Pinavia starts from the next operational question: what happens when that sourced answer needs to become a regulated decision with a named human accountable for the outcome?

Both theses agree that model capability alone is not enough.

Both care about verified context, source traceability, and model-agnostic infrastructure.

Both reject the idea that a generic chat window is enough for enterprise AI.

DimensionContext-memory infrastructurePinavia governed workflow infrastructure