OKAO Labs

Architecture

One decision engine. Instantiated per domain.

Every OKAO product is an instantiation of the same loop. What differs is the domain data, the constraint model, and the shape of the decision at the end of it.

The loop

  1. 01

    Intent

    What is actually being attempted

  2. 02

    Context & Data

    Domain signal, constraints, history

  3. 03

    Inference

    Models fitted to the domain

  4. 04

    Recommendation

    Ranked, explainable options

  5. 05

    Decision

    A human commits

  6. 06

    Outcome

    What the world returned

  7. 07↺ 01

    Learning

    Priors updated, loop closes

  8. THE LOOP

    Every domain we enter reuses this spine. Only the data, the constraints, and the shape of the decision change.

Same layer, different world

LayerShared mechanismResactlyEnergy
Intent captureA typed representation of goals, constraints, and tolerances.Occasion, party, budget, distance, dietary constraints, appetite for novelty.Load profile, siting envelope, reliability target, capital limits, timeline.
Domain data layerEntity graphs, normalization, and provenance per industry.Restaurants, menus, dishes, preparation, service patterns, behavioral signal.Generation, grid and interconnection, geography, fuel and market pricing.
InferenceModels fitted to domain structure, scored against realized outcomes.Dish-level affinity and match scoring under contextual conditions.Feasibility, cost-to-serve, and risk evaluation across configurations.
Recommendation surfaceRanked, explainable options with the reasoning exposed.A short list a diner trusts, with the reason it fits stated plainly.Comparable configurations with sensitivities and stated assumptions.
Outcome & learningThe decision and its result return to the system as signal.Visits, orders, repeat behavior — and demand intelligence for operators.Project progression, revised estimates, and post-decision reality.

Why this stays focused

A new domain is only worth entering when four conditions hold: intent is rich and currently unrecorded, the data is specialized enough that generic tools fail, a real decision sits at the end of the process, and the outcome of that decision is observable. Most industries fail at least one. The two we work in do not.

01

Intent is rich and unrecorded

02

Data is specialized and messy

03

A real decision terminates the process

04

Outcomes come back measurable

Resactly →Energy Infrastructure →