One intelligent layer for the work between your systems.
Adanse connects your business systems, knowledge and policies, then gives governed AI employees the ability to investigate, coordinate and complete operational work — with human oversight and measurable outcomes.
The sandbox opens with a pre-filled sample business — AI employees, live decisions, memory and graph — so you can explore governance in action before connecting anything real.
Connect → Understand → Operate → Govern → Improve
ERP, CRM, ITSM, HR, finance, email, documents and internal APIs.
Business context, memory, processes and policies — with provenance.
AI employees with roles, skills and defined authority do the work.
Every action earns permission: policy, risk, evidence, approval.
Time saved, cost avoided, errors prevented — fed back into learning.
Your systems work. The work between them doesn't.
Most functions are already digitised. But business work rarely stays inside one system — and the gap between them is where cost, delay and error live.
Who is the customer, what was promised.
Order, allocation, pricing, credit hold.
Stock position and warehouse status.
Exceptions agreed outside the systems.
Then decide, update the customer and the systems.
The individual systems are not the problem. The investigation, coordination and judgement between them is.
An AI employee never gets access to a system. It gets permission to do one thing.
Connecting Salesforce is not the same as allowing AI to act in it. Each connection is broken into business capabilities, and capabilities are granted individually with a risk class and value limit.
Horizontal platform. Packaged around real operational work.
A pack is configuration — AI employees, skills, automations, policies, evaluations and outcome templates — sitting on the same core.
Prove the value before anything is allowed to act.
Adanse watches the process, records what a human decided and what it would have decided, then reports the agreement rate and the value at stake.
Six boundaries. Every action sits on exactly one.
An AI employee never operates at an undefined level. R0 to R5 is set per remit, enforced at execution, and changing it is itself an approved, recorded decision.
Every action must earn permission.
Before an AI employee touches a system of record, the request is checked against identity, authority, capability, policy, risk and evidence — then allowed, sent for approval, or blocked.
Within capability, policy and risk limits. Executed and recorded.
Named approver sees the evidence, the policy and the value at stake.
Outside authority. Recorded with the reason, never silently dropped.
It reasons on your systems, not on a copy of the internet.
Bring in the tools your business already runs on. Everything an AI employee relies on stays inspectable, with provenance attached.
Salesforce
HubSpot
Slack
Xero
QuickBooks
Stripe
Google Drive
Gmail
Notion
Zendesk
Shopify
Jira
Dynamics 365 Business Central
Dynamics 365 Finance & Operations
Dynamics 365 Customer EngagementConnector coverage varies by plan. Anything not listed can be reached through the workspace API.
Six rules the product is built on.
Adanse operates across your systems rather than trying to replace them.
Connecting a system is not the same as granting AI permission to act in it.
Deterministic work runs as a workflow. AI is used where judgement is required.
Observe → Shadow → Recommend → Approve → Controlled → Autonomous.
Identity, capability, policy, risk, evidence, approval, verification.
Measure time, cost, revenue, quality, risk and operational improvement.
See it working before you connect anything.
Every new account opens in a pre-filled sample workspace: two governed AI employees, a live decision waiting on approval, business memory, the intelligence graph and a full audit trail — all enforcing the same R0–R5 controls as production.
Nothing in the sandbox touches your real systems. Propose, approve and reject decisions with zero risk.
Move between Production, Staging and Evaluation from the workspace menu — autonomy and policy travel with you.
Connect a real system from the catalogue and the sandbox becomes your first governed operation.
Show us one repetitive process that crosses multiple systems, requires investigation and creates measurable cost or delay. We will shadow it before it ever acts.