SenangAI: your data, your infrastructure, your control
SenangAI

Private, permission-aware AI for regulated enterprises.

Your data. Your infrastructure. Your control.

SenangAI connects your organisation’s knowledge, answers with citations, and runs approved workflows without moving sensitive data outside the infrastructure and regions you control.

On-premises · private cloud · sovereign region · hosted · multilingual

SenangAI / organisational memoryGovernance active
Request → policy → evidence

The Sovereignty Commitments

01 · Your dataIt runs inside your perimeterYour data centre, your tenancy, or a sovereign region. Retrieval stays local in every mode.
02 · Your modelsNothing runs unless you approve itRegister open-weight models on your own hardware, regional endpoints, or approved commercial APIs. Anything else is absent.
03 · Your rulesScope and approval are enforcedIdentity, scope, budget and human approval are checked before an answer is produced, not applied to it afterwards.
04 · Your proofIt can show what it didQuestion, sources, model, cost, approver and denied attempts are recorded as work happens, and can be exported for audit.

These four hold in every deployment mode. If any of them stops being true for your configuration, that is a defect, not a setting and not a tier.

The system

Your rules, enforced by architecture.

Approved knowledge enters through governed scopes, becomes organisational memory, and powers answers and action. Identity, scope, approval, budget and audit are checked before anything runs. Sources include files, drives, chat, wikis, databases and APIs. Permissions stay with the source.

SenangAI / platform architectureGovernance active
1Data sourcesConnect approved knowledge
Files & PDFs
Drives & suites
Chat & wikis
Databases
APIs & webhooks
2Governed scopesBoundaries at every layer
OrganisationEnterprise memory
TeamspaceShared, role-aware knowledge
PersonalPrivate context
Permissions · provenance · deletion
3SenangAI engineCited knowledge and controlled action
CiteApproveAuditScope
SenangAIAsk · see · connect · automate
4Business outcomesTrusted answers to safe action
Cited answers
Connected knowledge
AI assistants
Agents & workflows
Reports · APIs · institutional memory
Where it fits

You probably already have chat and search.

Keep them. SenangAI is the knowledge layer they can use when answers must stay inside permissions, show their sources, and wait for a person before they act.

Chat assistantsWrite well from the context they are given. They are not a system of record for company knowledge.
Enterprise searchFinds known documents and usually respects source permissions. It returns documents, not a governed answer.
Custom AI appsDo one job well. Permissions, evidence and audit are often rebuilt for each new workflow.
SenangAIConnects knowledge across sources, returns the evidence, and runs work under one scope, approval and audit model.

If chat or search already solves the job, we will say so in the first call. Use SenangAI when the source of an answer matters, the data cannot leave, or the AI needs to act. Chat, search and SenangAI, side by side →

The product

One governed system, five moves.

Automate work with a person in the loop. Ask and get proof. Keep every workspace inside its boundary. Build agents out of skills. Then see what the system is actually doing.

01 · Automate

Workflow with human approval

Build the flow. Pause before action. A person decides what runs.

01TriggerSchedule or request
02KnowledgeScoped research
03AgentDraft the work
04Human approvalReview and decide
05DeliverOnly when approved
Ready to run
02 · Ask

Answers with proof

Ask plainly, in any supported language. Get permitted answers with sources you can check.

What changed in Project Atlas?
Project brief · p.8Decision logBudget note
03 · Govern

Governed AI workspaces

Organisation, Teamspace and Personal scopes set what people and agents can see and do.

OrganisationCompany-wide
TeamspaceShared team
PersonalPrivate context
PeopleAgentsTools
04 · Build

Build your own agents and skills

Everyone starts with a personal agent. Teamspaces add as many as they need, and each inherits scope, audit and approval the moment it exists.

Contract ReviewerBorn paused
Read the contract
Compare to playbook
Draft the summary
Legal teamspace · 4 agents · unlimited
05 · Insights

See what the AI is actually doing

What people ask, which sources answer, where the spend goes, and which teams have adopted it.

Questions answered1,284
Answers with citations98%
Spend against budget62%

Sample console. Not a published customer result.

What an evaluation looks like

One use case. Three weeks.

Bring your compliance, risk and technology leads. Pick a question your organisation already argues about. We will show the governed answer and the evidence behind it. If you want the list before a call, use the three-week evaluation checklist.

Day one

First cited answers

Upload a folder or connect a knowledge source, set one teamspace boundary, and ask real questions. No admin project, no data migration, no integration work.

You see answers with sources attached
Week one

Scope isolation proven

Two teams, two boundaries. We show a question that returns nothing because it should, and the audit record the denied attempt produced.

Your risk lead sees it fail closed
Weeks two to three

One workflow in production

Build a workflow with a real approval step, run it against real work, and review the audit trail and the spend it consumed against budget.

You decide on evidence, not a demo
Live demo

See SenangAI with a question you already have.

Thirty minutes, run by a founder. Bring one use case. We will show a cited answer, a denied request, and the audit record.