Most "AI agents" are prompt chains in a trench coat. iii Agent Hub is a digital company: AI executives that set strategy, AI workers that prospect, sell, market & support — coordinating through one shared brain, bounded by a constitution, grading their own decisions. It doesn't answer prompts. It runs the business.
Autonomous by design · Accountable by architecture · Human kill-switch on every decision
A shared system of record, and a layer of governance. That's the gap between a demo and a business you can actually leave running.
Not a one-shot answer — a self-correcting cycle that closes on itself, every day, on real metrics.
Pulls real metrics per brand — pipeline, spend, conversion, health.
→Executives read the numbers against brand knowledge — gated on statistical significance.
→Acts on low-trust calls; escalates high-trust ones to a human approval queue.
→Sets targets & levers that flow to the worker agents who do the work.
→Logs a prediction, measures the real effect later, and grades itself. The loop closes.
↺Five AI executives set the strategy. Twelve specialists do the work. Every one of them logs to the same shared brain.
Finds, enriches, scores and reaches the right prospects across multiple sources — 24/7, on policy.
Alex · MorganHandles inbound, books calls, threads real conversations from the right identity — never off-brand.
Riley · SamPublishes search- and AI-discoverable content, comparison pages and campaigns that compound.
JordanCRO, CMO, COO, CFO, CIO set targets, allocate budget, and own the levers — like a real C-suite.
Reva · Margo · Otto · Cleo · IrisWatches for silent failures, grades performance, and enforces who's allowed to pull which lever.
Casey · Parker · QuinnCompetitive intel, product feedback, fundraising and engineering — the rest of the operating bench.
Blake · Dana · Avery · TaylorAnyone can wire up agents. The two layers below are what let you actually remove the human and scale.
Agents never call each other. They sense and act through a single shared knowledge fabric — a semantic graph, a brand KB, and an append-only ledger of every action with its cost and outcome.
Result: loose coupling, zero hidden state, and a complete audit trail of everything the company has ever done. graph_nodes · agent_actions · executive_decisions
Every lever — spend, outreach volume, pricing — has one owning executive. Try to pull a lever you don't own and the action is structurally blocked and converted into a cross-domain request. Humans can lock any setting; agents can't overwrite it.
Separation of powers + a human-overridable control plane + a self-grading decision ledger. human > agent > default
The system is multi-tenant by design — the marginal cost of the next business is data, not another team.
Holdcos, venture studios, agency networks and SMB roll-ups running a portfolio of businesses on a lean central team.
Post-PMF, pre-Series-A teams where the founder is the SDR, the marketer and support all at once.
Lower-middle-market funds whose thesis is "buy people-heavy SMBs, expand margin with AI."
Each decision is logged with a prediction. Time passes. The system measures what actually happened and corrects. Now multiply that across every tenant sharing one learning layer.
See the data flywheel →A closed causal learning loop — predicted vs. measured effect on a real P&L.
Cross-tenant meta-learning — what works for one brand lifts them all.
A data flywheel & network effect competitors can't simply buy.
Start with a two-minute conversation with our AI agent. If what you run is a fit, it books you a live walkthrough — discovery, outreach, replies and the decision ledger — with our team.
AI qualifies you in minutes · qualified operators get a live walkthrough · pricing is tailored on that call
Agent Hub