One agent across every system you run, with a memory that outlasts the conversation.
What follows is what a QuasiHuman operator is actually made of: tools that span your whole landscape, interfaces it builds for you mid-turn, three kinds of memory that survive the week, reflexes that take over the work it has already proven, every doorway it arrives through, and the runtime underneath all of it.
A single-system bot is a commodity. Reasoning across your whole landscape is the product.
The agent doesn't hand you between four bots. It reads the account, files the claim, checks the finance position and evaluates the policy inside a single conversation — carrying what it learned between each step.
Every system reaches it as curated, task-level tools: typed, classified by blast radius, every mutation gated. Not raw database access. Not screen-scraping.
It builds the interface, not just the answer.
When a paragraph won't do, the agent builds you an interface — a form, an approval, a triage queue — right inside the conversation. Ask for it once and it's saved: you reopen it months later on live data, with no model call anywhere on the path.
A surface is data, never code. The model authors a validated declarative tree against a closed component registry — no HTML, no iframe, nothing generated ever executes — and every capability it reaches is re-authorised against your policy on every call.
A worker is not a transcript. It's something that survives the week — and teaches the next one.
Kill the server mid-task. It resumes where it stopped.
Every conversation is a durable workflow, checkpointed at every step — and it never repeats the side effects it already committed. Work that parks for a human decision on Friday picks up on Monday holding everything it knew.
It remembers Tuesday.
Three kinds of memory — what happened, what's true, and how work actually gets done here — retrieved by meaning, keywords, entities and recency across four tiers. A procedure that works is kept as a skill, and every time it's used the outcome is recorded.
Or have us design routines with you from day one →What one person learns, the company keeps.
Agents maintain a knowledge base for your organisation out of the work itself — integration guides, process docs, why a decision went the way it did. Every page and every memory is authorised at query time against your hierarchy: level, team, role. Someone leaves; what they taught the system stays.
The first time, it reasons. The hundredth time, it just does it.
A skill is something the colleague has learned to do. A reflex is what that skill becomes once deciding again is a waste: the same tool calls, in the order that worked, replayed with no reasoning model in the loop. The tools were never the slow part. The thinking between them was.
Nobody writes the reflex. The work does.
Every run is recorded: the tools called, the order, the arguments, the outcome — failed runs included, because they are what stops a bad habit becoming a reflex. What repeats every time is kept. What only existed to decide the next step is dropped. Nothing becomes a reflex until a named human approves it.
Guided first. Alone once it has earned it.
A new reflex is handed to the model as a plan, and its adherence and success rate are measured while the model still drives. Only one that proves itself is promoted to run without it. An approved version is locked — a change is a new version, and a new approval.
Faster. Never more powerful.
Every step of a reflex passes the same policy check as any other tool call, before any side effect: allowed, refused, or held for a named human. Unexpected output, low confidence or a changed policy hands the task back to the model with the completed steps attached, so nothing runs twice.
Reflexes run on Cerebellum, the reflex runtime we built. It is part of QuasiHuman and runs in your account with the rest of the stack. It is also a product in its own right, for teams running their own agents on their own harness.
cerebellum.ioOne agent. Every doorway. The runtime is the product — the chat window is just one way in.
One script tag drops an agent into your own applications, authenticated against your service — not a third-party bubble in the corner.
Any upstream service, webhook or cron can start an agent run programmatically. No human has to be in the room for work to happen.
The agent perceives the page your user is actually on and acts on it with them — surviving navigation, asking before it touches anything.
When a paragraph won't do, the agent builds a small interactive interface in the conversation — and you can keep it.
Direct messages and channel mentions, streaming its answer into the thread where the work is already being discussed.
Embedded voice and inbound telephony on the same runtime — the caller talks to the agent that already knows the account.
Recurring agentic work on a schedule. The Monday reconciliation runs itself and only escalates when something looks wrong.
Agents with a mailbox: reading, searching, replying — and inbound mail that routes straight to the agent expecting it.
Not six chat windows. One runtime, with the parts a real operator needs.
It delegates, parks, and picks the work back up.
Big jobs fan out to specialists that run independently and report back. The parent waits without burning budget, then continues with everything the children found.
Goals that outlive the conversation.
A multi-step objective is a durable plan, not a prompt. It survives across days and chats, tracks its own dependencies, and reports progress against the outcome you asked for.
Reviewable output, not chat scrollback.
Work lands as versioned artifacts your team can diff, comment on, approve or roll back. The record of what an agent produced is a document, not a transcript you have to scroll.
It writes code, then runs it somewhere safe.
When the answer needs computation rather than a plausible-sounding paragraph, the agent writes code and runs it in an isolated microVM — no network trust, no access to your systems except through the tools you granted.
Bring us the workflow that nobody wants to own.
The platform earns its keep against a messy landscape, not a demo. Tell us which systems have to agree with each other and we will map the capability boundary with you.