What we deploy.
Six shapes the work usually takes. None of them is a product you configure — each is a forward-deployed build against your systems, your data, and your definition of done.
A go-to-market motion that runs itself.
Agents that research accounts, draft outreach, and keep your pipeline moving — so your team spends its time closing, not coordinating.
- Account research
- Adaptive outreach
- Pipeline hygiene
Every answer your company already knows.
A single intelligence layer over your documents, tools, and tribal knowledge — so anyone can get a grounded answer in seconds.
- Unified search
- Grounded answers
- Team copilots
Resolve more tickets, not just deflect them.
Agents that resolve customer issues end to end — grounded in your product and docs — with your team on the cases that need a human.
- End-to-end resolution
- Grounded in your product
- Triage & routing
Natural voice agents that get things done.
Real-time voice agents that answer, qualify, and resolve over the phone — grounded in your systems and handed off cleanly when a human is needed.
- Inbound & outbound calls
- Real-time conversation
- Task completion
Turn documents into structured, usable data.
Read, extract, and reason over the documents that run your business — contracts, statements, forms, and filings — at scale and with an audit trail.
- Extraction
- Classification & routing
- Validation & reconciliation
A custom agent built around your workflow.
When the off-the-shelf use case doesn't fit, we build an agent around your exact process — integrated with your systems and owned by you.
- Scoped to your workflow
- Connected to your systems
- Guardrails & permissions
If your problem is not on this list, that is not a problem. Most of what we build starts as a workflow nobody had a category for.
Book a callSix shapes, one set of rules.
Whichever of these a build starts as, the same four commitments apply. They are why the list above is a set of starting points rather than a product catalogue.
It runs against your systems.
Your CRM, your warehouse, your document store, your permissions — not an export, and not a sandbox copy that drifts out of date the week after launch.
It is evaluated before it ships.
Every deployment gets a harness that scores it against cases your own experts have judged. Without one you have a demo and an opinion, not a system.
It fails honestly.
The system says when it is unsure, escalates to a person, and leaves a record of what it did. Confident wrong answers are the failure mode that ends deployments.
You get the keys.
Prompts, evaluations, pipelines and data stay yours. If you decide to run it without us, the handover is a transfer rather than a negotiation.
Choosing the first one.
Almost every organization we meet could justify three of these. The order matters more than the choice — the first deployment is what buys the political room for the rest.
Start where the volume is.
A workflow that runs a hundred times a week produces evidence in a fortnight. One that runs quarterly cannot prove anything before the budget conversation comes round again.
Start where the standard is clearest.
If someone can tell you in one sentence what a good output looks like, that workflow is ready. If it takes a meeting to decide, fix that first — no model resolves an ambiguous standard.
Start where a person is the bottleneck.
The best first deployments relieve someone specific whose queue everyone can already see. It makes the result obvious without a dashboard, and it makes an ally of the person best placed to object.
What people ask before choosing one.
Can you combine more than one of these?
Usually it happens on its own. A knowledge deployment tends to grow a support surface; a document build tends to grow agents. We still ship them one at a time, so each has to prove itself.
How long until the first one is in production?
Weeks rather than quarters for a well-scoped first workflow. The variable is almost never the build — it is how quickly we can get scoped access to real data.
What if we already started building this internally?
Good. That is often the fastest engagement we run, because the hard thinking about the workflow is done and what is missing is evaluation, security posture and the last mile into production.
Do we need a data team before any of this works?
No, though you do need somebody who knows where the data actually lives and what is wrong with it. That person is worth more to a deployment than a data platform.
Or start from your world.
The same deployments, framed by the controls each industry actually has to satisfy.
Financial services
High-stakes workflows, automated with the audit trail and explainability your controls demand.
Healthcare
Take the administrative weight off clinical teams so their time goes back to patients.
Legal
The highest-volume, highest-leverage work — handled with your playbook, your standards, and a human on every output.
Real estate
Turn the documents and data behind every deal into a working, auditable asset.
SaaS
Agents grounded in your real product and systems, deployed in weeks, not a year-long project.
Recruiting & staffing
The repetitive, high-volume work behind every placement — handled continuously, with a recruiter on every decision that matters.
Not sure which one you are?
Describe the workflow and we will tell you which of these it really is — including when the honest answer is that it does not need AI at all.
Book a call