Let agents do the work.

Eight production agents move work between your peopleand your systems, on your own infrastructure.

See the 8 agents

Clinical Scribe · Healthcare

Running in production across 4 industries · Compliant by design

Who it's for

Find your team. See your before and after.

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.

  • CitationsEvery answer carries its source
  • Paragraph citesDown to the exact page and line
  • IntegrationsSAP · Drive · Slack · +22 more
  • GuardrailsSet fields, not free text
  • ConversationsAsk follow-ups in plain words
  • Honest gapsNot 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.

Compliance

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.

BLM+

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.

ValueMaxx, not TokenMaxx

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 out

Pilot. A handful of documents and users. At this size, either way of running AI is cheap.

CostPilotA few teamsDepartmentOrg-wide

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.

Lower running costSecure on your infrastructureAccurate at scale

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.

See pricing

Ready when you are.

Describe one workflow. We'll show you the agent, the price, and an honest go or no-go.