Specialist agent teams · imaaaas
Imago runs its own trading book, storefront, and operations on a persistent team of specialist AI agents. We package that team — governed, memory-keeping, human-in-the-loop — and set it up for your business.
The offer
Hand over a whole workstream, not a single question. An orchestrator and its specialists split the work between them and report back — the way a small company actually operates.
Persistent memory across sessions means no stateless catch-up every morning. The team wakes up knowing where things stand and picks up where it left off.
It asks before it acts on anything that matters. Earned autonomy, not autonomy by default — you get an operator you can trust, not a black box you have to babysit.
We didn't build a demo. This is the team that runs Imago's own trading, store, and operations — packaged for you. If we wouldn't run our company on it, we wouldn't sell it.
What we run
Every product below is operated by the same team we set up for customers. That's the whole pitch — we run what we sell.
Agent teams · flagship
Specialist agent teams as a product. A governed orchestrator plus specialists that run ongoing work — research, ops, content, monitoring — with you in the loop. We run our own company on it.
→ Learn moreVertical kit · AEC
A specialist team for structural / AEC work — construction drawings and Eurocode calculations. Our first design-partner deployment, live today with a real engineering firm.
Design partnerCommerce
A live storefront run end-to-end by an imaaaas team — content, compliance, and operations. The reference case for the marketing + compliance kits.
LiveTrading · research
A structural-edge trading book the team builds, validates, and operates itself — carry-first, hard-gated, honest about scale. Proof we run what we build.
LiveThe kit family
Same proven team at the core, tuned for your field — structural engineering, content and commerce, compliance, and more on the way. You pay us to set it up and keep it running, not for software: the kit itself is open.
The team
Founder
Biologist turned technologist. Sets direction, makes the final calls, keeps the humans-in-the-loop honest.
Orchestrator
Coordinates the team, makes operational decisions inside set boundaries, and forces the open questions to a call. The synthesizer.
Researcher
Web research, competitive analysis, data sourcing, fact-checking. Delivers verdicts with citations, not summaries. The generator.
Builder
Ships code, runs backtests, deploys, hardens the safety rails. Says "won't work" when it won't. The skeptic.
Yes — three of the four are AI agents, and we're transparent about it. The team runs at a pace a traditional structure can't match, with a human holding the wheel on anything that matters.
How we work
Ideas are cheap, execution is everything. Concept to running system in days, not quarters.
No fake metrics, no buzzword dressing. If something is experimental or AI-generated, we say so.
We pick problems worth solving. It doesn't need a billion-dollar market — it needs to be genuinely useful.
Eleven principles, one bridge
We build agent systems the way living ecosystems actually work. Each principle below pairs a mechanism nature evolved with the concrete mechanism our own systems use to mirror it.
01 · Lean energy routing
Energy flows one direction through the food web — only ~10% reaches each higher level. Ecosystems survive by being ruthlessly lean: filtering hard, spending scarce high-value energy only where it changes the outcome.
Our agents route work by cost — lean models handle scans, drafts, and extraction; the most capable models are reserved for judgment and capital-gating calls. We measure cost per meaningful output, not per task.
02 · Two-way information flow
Information cascades both ways through the web — a warning scent, a shared nutrient signal. Intelligence emerges from the network itself, not from any single organism holding the whole picture.
Every agent's output improves the next one's input. Research becomes a build spec becomes working code; one team's proven workflow becomes another's starting point instead of a problem re-solved from scratch.
03 · Loops that self-regulate
Ecosystems hold themselves steady through feedback — predators dampen prey booms, fertile ground amplifies growth. No central controller; the loops do the governing.
Human approval is our anchoring loop — a person signs off before anything customer-facing ships. Machine loops score work, revise, and re-check; compliance flags block, measured quality-lift promotes. Nothing fires and forgets.
04 · Diversity is resilience
A monoculture dies to a single shock; a diverse system routes around it. The loss of one keystone can cascade, so resilience is stored in variety and redundancy.
Our compliance gate runs two AI models from different vendors, so neither's blind spot slips a claim through. Data comes from multiple sources, never one; if a service fails, work fails loudly and falls back — never silently.
05 · Protect the keystones
A few species carry disproportionate weight — remove the sea otter and the kelp forest collapses. Healthy systems identify their keystones and protect them first.
We name our keystones — the orchestrator, the human-approval queue, the memory that carries context between sessions — and guard them explicitly. When an agent restarts, a verified handoff preserves its full state so nothing is lost.
06 · One job, emergent whole
Complex, adaptive behavior emerges from simple organisms following clear local rules — no ant designs the colony. Composition, not individual complexity, produces intelligence.
Each agent has exactly one job — one orchestrates, one builds, one researches, one questions. Complexity comes from how they compose, not from any single agent doing too much, so they combine in ways no one scripted.
07 · Steady small adjustments
Stability comes from continuous small corrections, not dramatic swings — a forest absorbs a dry spell through countless minor adaptations, holding equilibrium under stress.
We prefer gradual rollouts to big-bang launches, keep live systems untouched while building their replacements, and design transforms to fail open — degrading gracefully rather than blocking. Steady state over heroics.
08 · Nothing is wasted
On the forest floor nothing is trash — every fallen leaf and dead organism decomposes into nutrient for the next generation. Waste is just input in the wrong place.
A failed experiment becomes a logged verdict, not a discard; a rejected draft becomes training signal; a research finding becomes durable memory reused next session. Every output has a downstream consumer.
09 · Every agent a niche
Specialization reduces competition — two species sharing an identical niche can't coexist, so each evolves to fill a role no other occupies, raising the whole system's efficiency.
No two of our agents compete for the same task. Roles have clear boundaries and clear tiebreakers, so work flows to exactly one owner — even our channel etiquette keeps signals from overlapping into noise.
10 · Don't skip stages
Ecosystems mature through predictable stages — bare rock to pioneer moss to forest — each built on the stability of the last. You cannot leap straight to the climax.
We build in order: the shared engine before the specialized loops, a working core before advanced features, this site live before the next registry opens. We don't bolt climax-stage complexity onto a system still finding its footing.
11 · Human and AI coevolve
Species evolve in response to each other — flower and pollinator reshape one another over generations. Neither can be understood alone, and prolonged partnership makes both more capable.
Our products are built so prolonged use makes both sides better — not a human passively consuming output. You own and tune your own agent team: it learns your work; you develop new ways of working. Growth, not dependence.
Get in touch
If you run a business drowning in multi-tool busywork — or you want to see the setup before you buy — reach out. We start with a small number of design partners.