Deterministic AI for real business decisions.
Decisions by data, not by tokens.
Most "AI" tools guess the next word. We compute the next decision. WorldMind builds your company’s private decision model from your business data and runs deterministic mini‑programs—so pricing, inventory, and risk calls are traceable, auditable, and policy‑guarded. No black boxes. Works across: investing, healthcare, strategic risk, manufacturing, transport & fleet routing, warehousing & last‑mile, retail assortment & pricing, agriculture planning, physical security, and facility maintenance.
Why most AI stalls and how to move past pilots
Prototypes everywhere, decisions nowhere
LLM copilots look slick, but outputs shift with prompts and model updates. You can't reproduce key nunmbers, explain regressions, or pass an audit
Business risk: AI Slop > Work Slop
Confident text turns into risky actions. We stop this by grounding AI in your data and policies, and computing outcomes, not paragraphs.
Production discipline
Versioned mini-models, built-in evaluation, and governance deliver reliable, governed decisions—week after week.
The Patented AI Platform
Social-Object Data Model
Our ETL turns raw files and systems into social objects-products, customers, orders, stores, policies-linked like a real business, each link weighted by strength (recency, frequency, value). Social weights are fully engineered or configurable: you can set how much each signal matters per use case (e.g., revenue over recency for pricing; safety incidents over spend for maintenance). Decisions run on customised models, not on generic internet patterns.
Decision Objects
Small auditable models for specific calls-Promotion ROI, Safety Stock, Price Clearance, Risk Rules-as well as Investment Sizing, Human Capital planning, Strategic Risk threshold, Care Pathway triage, Maintenance windows, and more. Each has explicit inputs/outputs, formulas, and formulas, and policy guardrails.
Deterministic Runtime
Non-token reasoning (math & stats over your data). Every run logs inputs, policy hash, code version, and outputs for replay and audit.
How it works
Connect your data
ERP, POS, CRM, EMR, PLM, telematics, spreadsheets, PDFs. We lift it into social objects (products, customers, orders, assets, policies, people) with lineage and weights.
Choose decisions
Wide ranging from Promotion ROI, Safety Stock, Clearance-or define Investment Sizing, Workforce Planning, Strategic Risk alerts, Care triage, Maintenance windows. Each is a mini-program with clear inputs and math.
Set guardrails
Min margins, price floors, risk thresholds, clinical or safety rules, and approval flows. RBAC enforcement (role-based access control) applies on every run.
Run & explain
Deterministic compute produces the decision with one-page explanation any manager can read and sign off. When LLMs appear, it's for explanation, never the computation.
Improve safely
Champion-challenger, A/B, and sandboxed changes. If a decision improves KPIs, promote it; if not, roll back. Full provenance keeps changes auditable.
Integrate
Push decisions to productivity tools like emails, documents, calendars scheduling. Use decisions to orchestrate Agentic AI and automation via API and webhooks.
Trust, security, and governance
Full traceability
Every decision stores inputs, policy harsh, and code version. Reproduce any result. Explain any change.
Access you control
Role-based access control (RBAC) and Attribute rules (e.g. region, seniority, unit) ensure only the right people can run or view certain decisions. Per-tenant isolation. Data residency options.
Compliance-ready
Audit trails, PII tagging, redaction, retention controls. Aligns with AI Governance best practice.
FAQ
How is this different from a typical LLM app?
Our decisions come from deterministic computation on your data, not from token sampling. LLMs are used only as the conversational layer, never as the decision engine.
Can we bring our own math?
Yes. Encode your specific calculations as Contextual Compute modules, versioned, tested and governed. Plug them into the runtime on-the-fly.
What's a Decision Object?
A small, versioned decision model (e.g., Invest ROI) with strict inputs/outputs, formulae, tests, and policy guardrails. Reusable across customers.
Where do results go?
Decisions don't vanish; they upgrade your model. With a single source of truth (SSOT) for history and rules, future AI can execute reliably and make better decisions.
From AI that Generates,
To AI that Reasons.
To AI that Reasons.
We’ll review one real decision area in your business and show how to turn it into a reasoning model you can trust.