Decision infrastructure for product teams

Infrastructure for the work of deciding what to build.

Iridae connects product-market understanding, outcome forecasting, adaptive experimentation, and strategic planning into one Bayesian decision loop.

Evidence updates beliefs. Beliefs update forecasts. Forecasts update plans. Plans trigger the next thing worth learning. The result is not another tool for producing decision artifacts. It is the infrastructure that keeps product judgment connected to reality as conditions change, with every belief traceable back to the evidence that shaped it.

Shared belief, live forecasts, adaptive plans, fewer expensive surprises.

Research without the retainer.

Product signals, customer feedback, market data, competitor movement, and internal discussion, drawn from the systems where the work already happens, continuously update what the team knows. No retainer needed to refresh the picture, no synthesis deck arriving after the decision window has closed.

Forecasts return odds, not a dressed-up number.

Comparable cases, target-specific signals, and current evidence combine into a full outcome distribution: probability of hitting your target, downside if you miss, what evidence would need to shift for confidence to rise. Not a scenario memo. A decision surface.

Experiments aimed, not scheduled.

When confidence is too low to commit, the system identifies the evidence most worth collecting and triggers the right study: fielded, adapted, and resolved. Not scheduled on a calendar. Aimed at what the plan cannot answer.

Plans that adapt before it hurts.

Goals become a family of strategies tested under uncertainty, each scored by probability of success. Decision points, fragile assumptions, and trigger conditions are surfaced before commitments close, not in a follow-on strategy engagement after they have.

Not a stack of point solutions. A loop that compounds.

Product teams already do this work with analytics platforms, survey tools, BI dashboards, research retainers, forecasting engagements, and strategy advisory. Each piece in isolation, with evidence scattered across systems no single tool can see, and the plan never adapts.

Decision infrastructure isn’t a dashboard, a search bar, or a project tracker. Iridae replaces the stack with a loop. Intelligence runs continuously; judgement stays yours; the loop compounds as priors calibrate, comps sharpen, and memory accumulates. Every decision is stateful: what was believed, what evidence supported it, and what changed later, preserved for the team to revisit, audit, and learn from.

The seams between systems are typed contracts, not hand-rolled glue; uncertainty crosses boundaries mathematically, without translation. The same property that makes each system independently deployable makes them composable by your team’s code or by AI agents acting on the team’s behalf.

UX surfaces

Different decision moments need different interfaces: Daily work should come to the team, and deep work should open into a focused workspace..

Headless integration

Everything else: your apps, internal tools, workflows, and AI agents.

Resonant Whisper

Proactively engages wherever decisions get made: Slack, Teams, Jira. When a forecast, plan, or experiment needs your judgment, a focused thread opens with the evidence attached. Your answer routes back automatically. It replaces approval emails, status meetings, and analyst hand-offs with threads where every interaction is planned as typed steps and logged to a provenance chain.

Lucid Spire

For questions bigger than a thread. Plans, forecasts, experiments, and risks compose into one editable workspace. Drag a launch milestone two weeks right; the loop re-evaluates in place. Branch a sandbox; commit back when it’s worth keeping. Replaces scenario decks, board-review packs, and spreadsheet workbooks that go stale the moment they’re produced; every visible element traces back to its evidence, and the past is locked unless new evidence is attached.

API, MCP, and GraphQL

Give your tools structured understanding and mathematical grounding. Iridae sits behind your apps, workflows, and AI agents: called by your code or governed agents acting on the team’s behalf, and reading from the systems where your operating evidence already lives. REST, GraphQL, and MCP all come from one OpenAPI spec, with typed inputs and calibrated posteriors instead of point estimates an agent would have to defend. Tenant-scoped, logged, reproducible; bounded autonomy by construction.