Let agents do the work.
Eight production agents move work between your peopleand your systems, on your own infrastructure.
Clinical Scribe · Healthcare
Running in production across 4 industries · Compliant by design
Find your team. See your before and after.
People and agents, working side by side.
Invoices read, matched and posted, with the source attached.
Invoice Intelligence
Your team handles only the exceptions, and early-payment discounts stop slipping away.
See how it worksVoucher Matching
Six documents checked. One clean cross-border payment.
See how it worksEnterprise Document Intelligence
A private chat for all your enterprise documents.
See how it worksAn agent for every workflow.
Document agents
Read, match, cite and post. The eight below are live in production today.
Answers with receipts.
An agent is only as good as its proof. Every answer links back to the exact document and line it came from, and anything uncertain waits for a person, so work gets carried out confidently and accurately.
- Citations — Every answer carries its source
- Paragraph cites — Down to the exact page and line
- Integrations — SAP · Drive · Slack · +22 more
- Guardrails — Set fields, not free text
- Conversations — Ask follow-ups in plain words
- Honest gaps — Not in your files? It says so
Full control.
Agents that act need governance that holds. It's built in, not bolted on.
Audit log
Every agent action recorded: who asked, what it did, which sources it used, and when.
Permissions
The agent sees exactly the data you allow, with your existing RBAC and SSO deciding who asks what.
Human in the loop
Anything the agent isn't sure about goes to a person, one click to approve or fix.
Running-cost control
Cost watched from day one and managed for you, so the agent stays cheaper than the manual work.
Your IP stays yours
The models, the index and every output live on your infrastructure. Nothing accrues to a vendor.
No training on your data
Your documents tune your agent. They never feed anyone else's model.
Standards we work to.
The frameworks our controls and our build are measured against.
The full picture, deployment postures, audit trail, controls, lives on the security page.
Agents run on your native infrastructure.
Your servers or your cloud, never ours. Small language models tuned to your job by default, or plug in the model your team already trusts. The agents and guardrails are ours either way; your data never leaves.
Flat cost at scale.
Token-billed AI gets more expensive the more you use it. Ours doesn't.
Monthly cost to run (↑) as you roll out to more documents & users (→)
Scroll to roll outPilot. A handful of documents and users. At this size, either way of running AI is cheap.
Pay-per-token AI: every new document or user adds compute and API spend, so the bill keeps climbing.
Your Attentions agents: cost-effective to run on your own infrastructure, so the bill barely moves as you scale.
Pay-per-token AI · the usual way
One giant, general-purpose model billed per token. Every document and every user adds API spend, so the bill scales with your volume, forever.
Attentions agents · what we build
Small language models tuned to one job, or your own preferred model, running on your own infrastructure with citations and guardrails built in.
Cost-effective to run — and more documents and users barely move the bill. ≈10× cheaper to run at scale.
Start small. Scale when it pays.
A low-risk assessment first. Then one agent, live in 2-4 weeks, that pays for itself within months.
Ready when you are.
Describe one workflow. We'll show you the agent, the price, and an honest go or no-go.




