The platform

Schema in. Working business out.

The factory is one engine that takes a typed domain schema and deterministically generates whole applications — data layers, APIs, portals, forms, role-based access, navigation. Deterministic where it must be exact; agentic where judgment helps. Every output is measured in millions of lines and delivered in tenths of a second.

The moat's mechanism

Output = deterministic core + agent-resolved residual.

Determinism is a dial we push toward 100%. Every business rule we validate is compute you never pay for again.

Deterministic core — maximize

Byte-reproducible, zero-diff output straight from validated specs. It grows every time we capture a real business rule or structural constraint — driving keys, foreign keys, uniqueness. Zero AI compute.

Agent-resolved residual — shrink

The small, spec-underspecified deltas, resolved by a private stack-tuned coding agent on our own inference — reviewable diffs in a harness, not drift. Cheap local compute, not vendor tokens by the million.

The intelligence stack

Thirteen layers, from token I/O to generated UI.

Application layer

12

App UI

Generated components, dashboard widgets, schema designer, knowledge explorer.

11

Knowledge

Enterprise repository, brand guidelines, decision lineage, SOP library.

10

Agents

Virtual employees, RACI matrix, maturity model, KPI designer.

9

Compiler

Schema compiler, DDD domains, claims & row-level security, route generator.

Orchestration layer

8

Ingestion

Meeting recordings, phone transcripts, document parser, chat, EDI / CSV.

7

Retrieval

Embeddings, vector store, semantic search, crosswalk index.

Inference core · L0–L6

6

Governance

Evals, reward models, audit logs, rollout gates. Why self-grading fails →

5

Router

Pack selector, deterministic rules, learned routing, industry accelerators.

4

Tool / MCP

Action surface for live data and operations — CRM, ERP, data warehouse.

3

State

Shared objects, case state, intermediate math, session context.

2

Mempacks™

Domain overlays (LoRA / DoRA), versioned packs, signed deltas. Try one live →

1

Base LLM

The foundation model — general reasoning and language priors. Bring your own.

0

Token I/O

Prompt templates, chat formatting, decoding params, token streaming.

The engine room

The substrate under every brand.

The codegen engine

Template-driven generation from schema JSON to full workspaces — admin portals, data layers, migrations, schema-derived permissions, generated forms. A shared core the vertical brands fork from.

The orchestration platform

An actor-based, multi-model inference mesh with smart routing, capability registries, and an OpenAI-compatible surface. It powers the agents, the study sessions, and the maintenance harness. See the API → · Design it on ActorFlow →

The spec front door

Where specs are authored and validated. Every rule captured here widens the deterministic core — and cuts the compute anyone ever pays to regenerate the app.

The management cockpit

A clean two-tier surface across delivery and requirements — one backlog shared by agents and humans, flowing tasks from idea to reviewed pull request.


See what the factory would compile for you.

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