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Purpose-agnostic agents

One machine. Ten labels.

Six sockets — identity, behaviour, knowledge, tools, models, limits. What you slot into them is what the agent becomes. We have built specialised agents on this chassis, and we will build one around your work too.

Talk to us about your domainScroll the drawing.
  • Six surfaces, every agent
  • Any domain, same chassis
  • 170+ integrations
  • Governance never swaps
Sheet 02 — one chassis, any purpose · six surfaces in console order01 / 08
01

An agent, before it is anything.

Six sockets, in the console's own order. Empty, this is every agent on the platform — and not one of the six is a prompt box.

The chassis

Six sockets, and they never change.

This is the same spine the Agent Studio walks you through, in the same order. Everything a domain needs is one of these six — which is why there is no seventh surface for your industry.

Chassis — socket layout6 surfaces
01

Identity

a name, an avatar, a domain template

How the agent introduces itself, and the register it starts from. This is the part end users actually meet.

02

Behaviour

instructions + skills, loaded on demand

The system prompt, the instruction modules layered on top, and the reusable skills it carries or loads when a rule matches.

03

Knowledge & Privacy

which bases it reads, what gets masked

The files, bases and datatables it may reach — and whether personal data is masked before it ever reaches a model.

04

Tools & Integrations

scoped tools and MCP servers

What it may call, granted per scope rather than per agent. Native tools, sandbox tools, and any of 170+ integrations.

05

Models

an ordered stack, local or hosted

Not one choice but a fallback order. The default answers; the rest are tried behind it. Local models make it work air-gapped.

06

Limits & Budgets

step, call and token ceilings

Caps on steps, tool calls and tokens, plus a timeout. An agent that cannot run away is an agent you can leave running.

Every domain fits inside these six
The whole argument

What a purpose changes, and what it never touches.

This is the page in one table. Everything on the left is a decision you make per agent. Everything on the right is the platform, and it is identical whether the agent drafts court orders or matches invoices.

Swapped per purpose

Six cards. Yours to set, and to change later.

  • Its name, avatar and register
  • Its instructions and the skills it loads
  • Which files and bases it may read
  • Which tools and integrations it may call
  • Which models answer, and in what order
  • Its step, tool-call and token ceilings

Fixed by the platform

The chassis. Not configurable, and that is the point.

  • It runs inside your network, on your hardware
  • Role-based access, granted per group
  • Tenant isolation across agents and filestores
  • Every prompt, tool call and file access logged
  • Your data is never training data
  • One console, one set of controls, one audit view
Specialised, not siloed

As domain-specific as you like. Still one product.

An agent here can be every bit as specialised as a vertical tool; ours already are. What you avoid is what a vertical charges: a second vendor, a second boundary, a second governance model when the next use case arrives.

One deployment, many agents

The second use case is six more decisions inside the install you already have — not another vendor, another boundary and another audit surface.

The domain lives in the config

What makes an agent good at court orders, or at a support queue, is its instructions, its indexed corpus and its scoped tools. All three are things you own and can change without us.

Governance does not fork

Ten agents across five departments still answer to one IAM policy set, one audit trail and one boundary. Approve the platform once and the tenth agent is a change inside something already approved.

We do run agents of our own — medical document intelligence, compliance, media — and every one of them was built on exactly the six surfaces above, using nothing you cannot use.

Where you point it

None of these needed a different product.

Five industries and five departments. Most organisations recognise three or four of them at once, and that is the case this page is built for: the fourth one costs six decisions, not a fourth procurement round.

Built to order

Want it specialised? Tell us the work.

Some teams want the chassis and their own hands on it. Others want the finished agent. Both are the same product: we walk the six surfaces against your domain, prove it on your own material, and hand it over configured.

Build request — specialised agentRef · your domain
  1. 01

    Describe the work

    What arrives, what should leave, and who signs it off. Plain language is enough — no specification document, no schema, and no integration audit before we start.

  2. 02

    We fill the six

    Instructions and skills written in your vocabulary, your corpus indexed and scoped, the tools it may call, the model stack behind it, and the ceilings it works inside.

  3. 03

    Proved on your own material

    A proof of concept on real work, running inside your own network: your documents, your queue, your questions. Not a hosted sandbox with sample data.

  4. 04

    Handed over, still yours

    It arrives configured, not locked. Every one of the six surfaces stays editable in your console afterwards, by your team, without us.

Same six surfaces · same deployment · yours to edit

This is not a services contract with a services team attached. The build runs on your own material inside your network, and what you are left holding is an ordinary agent in your console: six surfaces, all editable, none locked to us.

What this changes

The first agent is a project. The tenth is a decision.

The first carries the cost of arriving: the install, the security review, the integration work, the argument over where data may sit. Every agent after it inherits all four. What remains is six cards inside an approved boundary, and the question becomes not whether the work justifies a vendor but whether it justifies six decisions.

A department can have an agent of its own without a supplier, a boundary or an audit trail of its own.

What you learn on the first agent is spent on the second. Instructions, corpora and skills are written once and carried across.

Work too small to survive a procurement round becomes worth automating. There is usually a great deal of it.

At a glance

The chassis, in specifications.

Surfaces per agent
Six — identity, behaviour, knowledge, tools, models, limits
Instructions
System prompt + layered modules + skills loaded on demand
Knowledge
Filestore, bases & datatables, knowledge graph
Tools
Native, sandbox, and 170+ MCP integrations
Models
Ordered fallback stack — local or hosted, per agent
Limits
Step, tool-call and token caps, plus a soft timeout
Isolation
Per group, per agent, per filestore
Delivery
Web chat · Slack · browser extension
Languages
Multilingual
Deployment
The same on-premise install, whatever the purpose
Questions

What people ask before they pick.

Can you build an agent specialised for our domain?
Yes. It is a normal engagement, not a special case: our own medical document intelligence, compliance and media agents were built the same way. We walk the six surfaces against your work, prove it on your own material inside your network, and hand it over configured. Every surface stays editable by your team afterwards.
Then why not just sell a product built for our industry?
Because the part that has to match is your organisation, not your sector — two hospitals do not code referrals the same way, and a vertical product's head start on the instructions and the corpus runs out quickly. What it does lock in for good is the boundary, the governance model and the roadmap.
What genuinely differs between a court agent and a support agent?
Six things, all of them settings: its name and template, its instructions and skills, which corpus it may read and what gets masked, which scoped tools it may call, which models answer in what order, and its ceilings. Nothing else. Same runtime, same permission model, same audit trail, same console, same install.
Do we have to write prompts?
You write instructions, which is a different job and a smaller one. Behaviour is layered: a system prompt, instruction modules on top, and skills the agent loads when a rule matches. Most of the work is describing when something applies, not composing one long prompt. Skills are written once and shared across agents.
Can one deployment run agents for different departments without them seeing each other's data?
Yes, and it is the normal case, not a special configuration. Access is granted per group, agents are scoped to specific filestores and bases, and effective access is the union of attached policies with deny overriding allow. An agent cannot read a corpus it has not been granted, whatever it is asked.
What can't an agent do here?
Anything outside its scopes and ceilings. The rest is guards you write: our agents extract and cite rather than give clinical advice, match and flag rather than post to a ledger, draft rather than decide. An agent is as narrow as its instructions and its scopes make it, and narrow is usually what you want.
Specified

Bring us the eleventh.

Whatever the eleventh turns out to be, it is the same six decisions and the same deployment underneath them. Nothing about it starts from scratch.

Book a demo
Exemplary AI — agent chassis
Surfaces
Six, fixed
Domains
Unbounded
Governance
Not configurable
Deployment
Yours
Specialised
By configuration