AI that can handle whole multi-step jobs, such as reading documents, transcribing and summarising conversations or translating content, with your people approving anything important.
Typical engagement10–16 weeks to first production use
SurfacesOrchestration service, review console, API
Proven onSabha Record — live legislative proceedings
ConstraintA person signs off anything that enters a record
What it means for your business
Hours back every week
Knowledge work that took a team days is done in minutes.
Voice and language
Speech-to-text, summaries and translation for multilingual customers.
Safe by design
Human sign-off and a full record of what the AI did.
Ideal for
Teams drowning in documents, calls, reports or multilingual content.
For your technical team
Multi-step AI systems that plan, call tools and act — with a gate wherever the output carries consequence, and an evaluation harness so accuracy is measured rather than asserted.
The problem
Why most agent projects stall at the demo
An agent that works in a notebook and an agent that can be trusted with a real decision are different systems. The gap is not model quality — it is everything around the model.
One model is asked to plan, retrieve, decide and write. It does all four adequately and none of them well.
There is no gate, so the first confidently wrong answer reaches a customer, a payment or a public record.
Nobody can say how accurate it is, because nothing was ever measured against a held-out set.
When it fails there is no trace, so the failure cannot be reproduced or explained to the person it affected.
How we build them
The gate is not a temporary measure until accuracy improves. Where an action is irreversible, it is permanent — and it is the reason a legislature was willing to put our output into its record.
What you get
Deliverables, not activities.
Each of these is something that exists at the end and that you own.
01
Task decomposition and planning
A request becomes an explicit plan the system can validate before executing, rather than a single opaque generation.
02
Tool and system integration
Typed tool schemas against your real systems — databases, internal APIs, document stores — with failure handling for each.
03
Retrieval over your own material
Grounding on your documents and records, with citations back to the source so an answer can be checked.
04
Human review consoles
The surface where your team approves, corrects or rejects. Designed for someone doing it two hundred times a day, not for a demo.
05
Evaluation and regression testing
Held-out sets, scored runs, and a regression suite so a prompt or model change cannot quietly make things worse.
06
Tracing and audit
Every run recorded: inputs, plan, tool calls, model responses, who approved what and when.
Technology
What this runs on.
Grouped the way a technical evaluator reads it. Everything listed is in production in work on this site.
The three things that decide whether this goes well.
A task that is genuinely repetitive and genuinely consequential — those are the ones worth automating.
Access to the systems the agent will need to read from and act on.
A person who can define what a correct outcome looks like, and who will sign off during the pilot.
Questions we get asked
Can the gate be removed once accuracy is high enough?
For reversible actions, yes — we usually start gated and relax as evidence accumulates. For anything irreversible or on the public record, no. That is a deliberate design position, not a limitation we intend to engineer away.
Which models do you use?
Whichever measures best for each task, which is why routing exists. We keep model choice swappable so that a better model next quarter is a configuration change rather than a rebuild.
Where does our data go?
Stated per engagement in writing, and honoured in the deployment topology. Where residency is a requirement — as it is for legislative data — we design to it from the start rather than retrofitting.
Start here
Let’s build what’s next.
Tell us where your business wants to grow. In one conversation we will show you where AI and software will pay back first, and whether we are the right team to build it.
We look at your goals, your current systems and your biggest time and cost drains, then recommend the first AI or software move with the fastest payback.
