Hand it off. It gets done. AI agents on your business data, inside your workflows and policies, with you in the loop.
Invoices chased, quotes drafted, customers answered, risks flagged. You approve what matters.
Activates on demand
Nine routine blocks moved off the calendar to the agents. One, approving quote Q-221, stays with you.
- Finance
- Reconcile · chase invoices
- Sales
- Follow up quotes
- Ops
- Re-key orders
- Support
- Status emails
- You
- Approve quote Q-221 Needs you · approve
- Hours back this week
- 23
- Waiting on you
- 1
What you get back.
Every department gets hours back.
Finance · operations · support · sales · custom agents
Ask the business. Get an answer.
Executive copilot · plain-English Q&A
You choose what waits.
Human in the loop · sign-off on sensitive actions
Every run on record.
Observability · a run history your team can review
Inside the limits you set.
Routine runs. Decisions reach you.
- Context scoped to your companyScoped
- Tools and ERP orchestratedConnected
- Approval rules for sensitive actionsEnforced
- Layered prompt-injection defensesLayered
AI went from answering to working.
Five shifts from the past year, and how we use each.
Agents that act, not just chat
What changed
Reasoning models now plan, call tools and check each result.
What it makes possible
- Back-office work done end to end
- Staff review exceptions, not routine steps
How we use it
Department agents run multi-step work on your ERP data, pausing where you require approval.
Example (illustrative)
The Finance agent matches payments to invoices and drafts follow-ups.
Open standards for tool access
What changed
The open Model Context Protocol standardizes how agents reach tools.
What it makes possible
- Connect systems without one-off integrations
- Swap AI models without rebuilding connectors
How we use it
Defined tools on your ERP, CRM and finance modules, scoped to your company.
Example (illustrative)
The Sales agent checks stock and pricing, then drafts a quote for approval.
Context that carries over
What changed
Agents now keep scoped memory across sessions instead of starting from zero.
What it makes possible
- Policies and past corrections carry forward
- Long tasks resume where they left off
How we use it
Agents ground their work in your own customers, orders and invoices.
Example (illustrative)
The Support agent reads past tickets and contract terms before drafting a reply.
Agents tested like software
What changed
Teams now test agents on real tasks, with graders and human review.
What it makes possible
- Measured quality before going live
- A clear signal for more autonomy
How we use it
Recorded runs let us check workflows on real cases before autonomy expands.
Example (illustrative)
A collections agent replays last quarter's overdue invoices. Its drafts get graded.
Layered defenses
What changed
Prompt injection is a top-listed agent risk. There is no single fix.
What it makes possible
- Read email and documents with less risk
- Payments and outbound messages can wait for sign-off
How we use it
Company-scoped tools, human approvals and recorded runs. Layers, not one filter.
Example (illustrative)
A vendor email hides a bank-detail change. It is held for a person to approve.
Live in 30 days. Billed monthly. No setup fee.
A free 30-minute call. We map your operation and work out what it's worth to you.
- Live in about 30 days
- Unlimited builds
- Month-to-month