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Discuss your project

Our approach

Agents that connect to your systems, work through complex workflows ahead of time and bring your people the answer. Through conversation, voice or an app built for the job.
Adjectiveapt, suitable, fit (for), good (for), appropriate, adept
{Apt・a}

Pre-emptive agents are the next step for AI in business

Large Language Models are excellent with language, but on their own they wait to be asked, can't handle every type of data and struggle with reliable multi-step reasoning. Our agents do the work ahead of time.
Apta AI technology chip representing advanced AI processing capabilities
Most chat assistants can only handle part of this
Large Volumes of TextLive Data FeedsLarge Structured DatabasesImages, Audio & VideoCharts & Diagrams
Pre-emptive
Chat Assistant
Which of our contracts renew this month on unusual terms?
Pre-emptive Process:
Read every contract as it arrives ⟶ check the renewal terms against your playbook ⟶ flag the changes before anyone asks
Prepared at 07:30, before you asked
3
contracts need a decision
RenewalsThis monthReplies drafted
Chat Assistant Process:
Waits for the question, then predicts a likely answer without reading your contracts
Most commercial contracts renew automatically unless notice is given, with notice periods typically between 30 and 90 days. To find out which of your contracts renew this month, review the renewal clause in each agreement or ask your legal team to check.
In our systems, language models handle the conversation. Specialist agents do the analysis and reasoning.
01 / Problem
Language models predict the next word. They are not built for exact logic or rule-based tasks, and on their own they miss the deep insights in large amounts of business data.
Problem
02 / Solution
We use language models to understand each request and write the answer, and pass the real work to an array of specialist agents and models, each built for one task.
Solution
03 / Our Edge
Our technology builds on PhD research from the University of Cambridge, including our team's work on hallucination detection, evaluation and agent safety. We design teams of specialist agents with careful routing and task decomposition, test them on your data and keep them working ahead of time, so they can be trusted with real work.
Our Edge
General-purpose AI has limits in specialised work.
Ask a general-purpose assistant a real business question and it hits the same problems every time: it can't see your data, it has no specialist tools and it only starts work once you ask.
“Which of our suppliers are exposed to this morning's price moves?”
Found Multiple Problems
No access to your own data
Your supplier list and contracts
Live market prices for every holding
No specialised agents
Matching suppliers across data sources
Calculating exposure exactly
Nothing prepared before you ask
Built to pass your security review
Tested on your data before we build, against measures agreed with your team
Runs in your cloud or ours, in UK or EU regions, with private models where data can't leave
Every step logged and traceable, with a person approving what matters
Questions We Get Asked
What buyers usually want to know first
How long does a project take?
Usually two to three weeks to scope, four to six weeks to a working prototype on your data, and three to six months to production. It depends on the scale of the project, and we agree the timings up front.
Which models do you use?
Whichever works best for each step. We use frontier models from Anthropic, OpenAI and Google, open-weight models that can run in your own cloud, and small models we train for specific tasks. We can swap a model when a better one comes out.
Can it run in our own cloud?
Yes. We can deploy in your own cloud account, in UK or EU regions. Where data can't leave your environment, we use open-weight models on your own infrastructure.
Who owns what you build?
You do: the code, the prompts, the test sets and any models we train for you.
How do you check the answers are right?
Before we build, we agree with your experts what a good answer looks like and turn it into tests. We run those tests throughout the project and keep running them once the system is live.
Do you only work in certain industries?
No. We have built products for financial markets, retail, media and education. What matters is a real workflow, real data and a clear way to measure success.
We build AI for specialised work.
Frontier models from Anthropic, OpenAI and Google are a strong starting point. We combine them with open-weight models, specialist agents and your own data, and test everything on your real workflows before it goes live.
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