Stagecell
Where Red Cell builds agents that earn autonomy.
One practice
Recursys and Atlas were not built twice. One practice builds every agent Red Cell ships, and it is available to clients.
We call it Stagecell. Service-desk agents, diligence agents, operations watch agents, document pipelines: anything with a mandate, built like infrastructure and promoted like staff. An agent starts with a written brief, works from your data, has its output checked by an independent model, and acts alone only after recorded evaluations say it is ready.
How you build one
Define it on a canvas. Ground it in your corpus. Let determinism hold the line.
Mandates are assembled visually: drag the permissions, tools and knowledge an agent may use onto its canvas, and the mandate becomes a contract the runtime enforces. Context is attached, not imagined: your documents, your systems, retrieval the agent must cite. And wherever a number or a rule matters, deterministic code does the work. The model narrates, argues and drafts, but it does not decide what is true.
Drag and drop the mandate together: scope, tools, knowledge, escalation paths.
Your corpus, ingested and retrieved with a relevance floor. No citation, no claim.
Rules, calculations and thresholds run as code, never as model opinion.
A separate model reviews every output against the evidence before it ships.
The proof: Atlas
Atlas is a Stagecell agent in production: an autonomous service desk with a second opinion built in.
Atlas takes a customer message from web, email or Microsoft Teams, works out what it is about, and drafts an answer grounded in the knowledge base. An independent judge reviews the draft against the evidence, not the reasoning that produced it. When a request needs action, the action is governed and tiered. When it needs a person, Atlas hands the conversation to a named human with full context. And because state lives in the database, a crash or deploy mid-conversation loses nothing.
Every message walks the same nine gates. No shortcuts, even for easy questions.
Receive
A customer message arrives from the web widget, email or Teams.
Guard
Injection attempts and unsafe content are stopped at the door.
Triage
Atlas works out what the message is about and what it will take to answer.
Retrieve
Evidence is pulled from the knowledge base, with a relevance floor it must clear.
Resolve
A draft answer is written against the evidence, never from memory.
Judge
An independent model reviews the draft against the evidence. No pass, no send.
Act
Approved actions run against your systems, governed and tiered.
Style
The reply is tuned to your voice without touching the facts.
Respond
The customer gets an answer, or a named human gets the conversation with full context.
Earned autonomy
Four gates between an idea and an agent you can trust.
Define the mandate
What it may read, what it may do, who it answers to. Written down, scoped, owned by a named person.
Ground it
The agent works from your data with retrieval it must cite. No citation, no claim.
Verify independently
A separate model checks its output before anything ships. Evaluation harnesses score it continuously.
Earn autonomy
Shadow first. It acts alone only after recorded evaluations say it is ready, and the audit trail never stops.
Scoped permissions and a named accountable owner.
Your knowledge base, cited in every output.
Independent judge models and evaluation harnesses.
Shadow first, autonomy after recorded green runs.
Bring us one process you wish ran itself. We will tell you honestly whether an agent should.
Schedule a Consultation