Superagents
Business-agent infrastructure — any goal, any system
Superagents is the infrastructure we built to stand up serious business AI agents fast — for any goal, wired into the systems a client already runs. An agent here isn't a single model answering; it's a coordinator that convenes a panel of specialist agents, runs them in parallel, and merges their work into one verified answer with a confidence score. It remembers what's already been decided, so it never re-raises a closed question, and everything that reaches a live channel passes a safety layer first. The first client is already in production.
- Industry
- Applied AI — internal infrastructure & client builds
- Year
- 2026
- What we ran
- Concept, architecture & infrastructure build
Parallel specialists converge on one answer with a confidence score
A new agent for a new goal — live in days, not a rebuild
The first client is already live on the infrastructure
The problem
A single-prompt agent is fragile for real operations: it answers from one point of view, forgets prior decisions, has no check on its own output, and can't be trusted to message a customer unattended. Serious work needs parallel expertise, verification, memory of what's already settled, and a safety boundary — without rebuilding all of that from scratch for every new agent.
How we solved it
We separate what an agent does from how it thinks and connects. A coordinator convenes specialist agents that deliberate in parallel; a synthesis-and-verification pass merges them into one answer and calibrates its confidence score; a decision memory keeps settled questions closed; and a safety layer guards anything sent to a live channel. On top sit autonomous, scheduled agents that monitor outside sources and push updates. A new agent for a new goal is a configuration on this infrastructure — live in days, not a project from zero.
What it does
A coordinator convenes a panel of specialist agents that deliberate in parallel — not one model answering alone.
A synthesis-and-verification pass merges their work into a single answer with a calibrated confidence score.
A decision memory keeps settled questions closed — the system never re-raises an option that was already rejected.
Connected to the client's system-of-record and messaging channel, with a safety layer on everything that goes out.
Autonomous scheduled agents monitor outside sources and push updates — with a person always in command.
Under the hood
- Multi-agent council with verification
- Decision memory & precedence
- Connector layer + system-of-record
- Safety-filtered channel & scheduled autonomy
What would your expert team take on?
Tell us the work that eats your week. We'll show you which AI expert takes it off your plate — working inside your existing systems — and what it saves you.