DcisionAI Book a decision ↗
Provable, not plausible.

The Intelligent Decision Layer.

DcisionAI turns organizational context into governed, explainable decisions with mathematical proof, traceable tradeoffs, and institutional memory.

See it on your data ↗ Explore the decision layer ↓
ContextOptionsResolveEncode

Systems of record preserve data. Systems of intelligence generate recommendations. But the consequential decision itself still lives outside the stack: in a spreadsheet, a meeting, a specialist model, or someone’s head.

DcisionAI closes that gap. It turns organizational context into optimized, explainable, and executable decisions, then writes the proof, tradeoffs, authority, and outcome back into institutional memory.

What we’re building

One decision plane for consequential work.

DcisionAI sits between the systems that know what is true and the systems that act. It turns organizational context into a governed decision, exposes the proof boundary, then writes the outcome back so the next decision starts smarter.

Inside the decision plane

Context graph

The organization becomes part of the model.

What it does

Captures how the firm actually works — roles, rules, systems, and prior decisions — so every new decision starts with the right context.

How it works

DcisionAI assembles the context relevant to the decision, including who owns it, which rules govern it, what evidence matters, and which prior decisions should become precedent.

Value

Start from how the firm actually works instead of rebuilding context from scratch for every consequential decision.

Formulation

Intent becomes a faithful mathematical problem.

What it does

Turns what you want to achieve into a clear problem the business can review before anything runs.

How it works

Structured translation and verified modeling layers make the formulation inspectable before solving, so a mathematically correct answer cannot hide a wrongly framed question.

Value

Review what the system is actually optimizing before trusting the answer. A right answer to the wrong problem is still wrong.

Optimization

Search the feasible space, not the model’s intuition.

What it does

Finds the best feasible answer under your real constraints — not a plausible guess.

How it works

The solver returns an optimal answer where proof is available, an infeasibility diagnosis when no valid answer exists, or a feasibility reference with its proof boundary explicit.

Value

Know what is best within the model, which rule is binding, and what each tradeoff is actually costing the organization.

Certification

A model proposes. Authority certifies.

What it does

Puts the final call with the person who has authority to approve, change, or reject it.

How it works

The approved formulation, evidence, solver result, unresolved judgment, authorized actor, and timestamp are captured as one governed decision record.

Value

Delegate more decision work without pretending human judgment disappears from high-stakes enterprise operations.

Traceability

Every answer carries the chain that produced it.

What it does

Shows why the answer was chosen — the context, rules, tradeoffs, and who signed off.

How it works

Each step is retained as a replayable trace rather than scattered across spreadsheets, meeting threads, prompts, and one-off specialist models.

Value

Move from “trust me” to inspectable evidence appropriate for operators, clients, compliance, and audit.

Decision memory

Every resolved run makes the next one richer.

What it does

Remembers how the firm decided, so the next decision doesn’t start from scratch.

How it works

The next decision inherits the organization’s accumulated operating context instead of starting from an empty prompt or a departing expert’s memory.

Value

Build a proprietary record of how the enterprise actually decides, one governed and provable decision at a time.

The solutions

Value by seat
across the firm.

Pick a role. See what changes for them: the value, the DcisionAI models that decide, and the productivity tools that draft from the decision trace.

01

Lead Advisor

Owns the household relationship and the fiduciary call.

Industry pattern

6.4 hrs/week assembling context before a decision. 1 in 5 client recommendations reworked after trading or compliance review.

Decides

    DcisionAI resolves

      Business impact

        Models that decide

        Each model resolves a bounded decision against the role’s real objectives, rules, and operating context. The language model can select and compose approved primitives; it does not invent the math.

        Drafted from the trace

        The decision is the source of truth. Productivity tools turn the decision trace into the communication, documentation, and handoffs the role already has to produce.

        The defensibility

        Two moats.
        One proves. One compounds.

        Each decision stands on its own math. Together they build a record no competitor can copy: how your firm actually decides.

        01

        Grounded in the math

        No hallucinated equations.

        AI composes from frozen, established optimization primitives. It does not invent the mathematical path and hope the result looks reasonable.

        02

        Decision memory

        The context your decisions reason from.

        Every run leaves behind a trace: roles, rules, evidence, binding constraints, authority, precedent, and outcome. Those traces become the context for the next decision.

        Research

        Research for organizations
        that must decide.

        Original thinking at the intersection of systems, intelligence, and judgment, built for leaders who face consequential decisions.

        ⌘SystemsHow organizations encode and operate. ◎DecisionsHow consequential decisions are made. ◇MethodologyThe models, methods, and evidence. ♙GovernanceTrust, accountability, and oversight.
        Featured researchInfrastructure · Medium

        Beyond the Spreadsheet:
        The Rise of Decision Infrastructure.

        Spreadsheets gave every analyst a calculator. Decision infrastructure gives every team a solver and a context graph.

        Read the research ↗
        Recent research Browse archive →
        Infeasibility

        The Error Message That Changed How I Think About Decisions

        ↗         Foundations

        Demystifying Mathematical Optimization

        ↗         Agentic AI

        Mathematical Optimization in the Age of Agentic AI

        ↗         Applied

        Optimizing for Success: Mathematical Optimization for E-commerce

        ↗         Architecture

        The Headless Enterprise

        ↗         Cognition

        The Institutional Ceiling

        ↗

        Ready when you are

        Bring one decision.

        Leave with the strongest answer your constraints allow, the proof behind it, and a trace your organization can use again.

        Book a decision ↗