Operate the full product loop
Tired of prompting
“Your last change broke checkout. Fix it now.”
We built a deterministic review loop instead.
Demiourgos maps how your codebase actually works together. When something changes, it can trace which routes, services, utilities, and product flows are connected to that change instead of treating the task like an isolated file edit.
That means the AI is not just writing code and hoping it works. It can see what a change is likely to affect, what could break next, and whether the result still matches the product behavior you actually wanted.
We surface only what is impacted, allowing you to review the exact logical move, not just a raw file diff.
Business Intent
“Update razorpay client to handle asynchronous webhook refunds safely without dropping active sessions.”
Impact Validation
billing/razorpay.ts
Logic ModifiedImplemented async webhook handler for refunds.
payments/checkout.ts
Downstream RiskCheckout session validation previously dropped async state.
api/webhooks.ts
Auto-ResolvedSignature validation dynamically bridged to preserve checkout session state.
Documentation
Let us document
your system with graph-native memory.
Product specs, runbooks, decisions, and architecture notes are ingested as structured project context.
Skills
Install a skill. The model knows the domain.
Razorpay becomes a live node in the graph. The model reads from it on every task — no manual context pasting.
No prompt stuffing
Structure loads before generation. No manual context pasting.
Integration accuracy
The model knows working patterns, shapes, and expected flows.
Evolves with approvals
Your decisions shape how the skill behaves on every task.
Self Product Evolution
User Feedback becomes verified upgrades.
User reports incoming
Humans manually flag production friction. The system ingests the raw context directly.
Structured Memory
One graph. Every connection visible.
A multi-layered, traversable ontology where business intent, human reasoning, and raw code all live in one interconnected graph. Hover any node to trace its connections.
Optimistic possibilities
An infinite loop of context accumulation.
The Demiourgos graph doesn't just understand your code — it can understand your entire engineering operation. The more it connects, the more deterministic it becomes.
Slack
futureUser complaints, incident alerts, and team discussions flow directly into the graph as contextual signals.
Jira
futureOpen tickets, sprint priorities, and bug reports are mapped against your codebase's logical impact graph.
GitHub
futureEvery PR, commit, and review comment enriches the graph's understanding of code evolution patterns.
Notion
futureProduct specs, architectural decisions, and roadmaps ground the graph in documented business intent.
Linear
futureEngineering cycles, feature requests, and velocity data inform the graph about product momentum.
Execution Loop
The loop that makes
autonomy shippable.
Receives the task, gathers context from the Alloy Net, and dispatches to the Worker.
The Brain + Hands execute: generate code, run tools, produce a draft output.
Evaluates output against policy, tests, and graph constraints. Decides pass or retry.
Why Demiourgos
Why this changes software delivery.
Demiourgos is more than an assistant. It is a platform layer that makes LLM-driven software execution more structured, more reusable, and far easier to govern.
Structured memory
Graph-native contextDemiourgos keeps code, product context, skills, reports, and decisions connected in one system instead of depending on raw prompt stuffing.
Skills
Reusable capabilityIntegrations become reusable graph nodes that can be activated, updated, and governed instead of rediscovered on every task.
Human gate
Controlled autonomyThe platform can move fast, but approvals, escalations, and shipping decisions stay visible and intentionally human-verifiable.
MCP native
Extensible executionDemiourgos can cooperate with MCP servers and external tool surfaces to manage knowledge, integrations, and workflows beyond the repo.
Execution proof
Operational confidenceTesting, review context, API chains, and release evidence are part of the product story, not an afterthought bolted on later.
Shipping system
From request to releaseDemiourgos can listen to feedback, plan changes, coordinate implementation, validate outcomes, and prepare shipping with less manual orchestration.
Platform Architecture
One execution platform. Three live systems. One human gate.
Demiourgos keeps reasoning, execution, and memory in one operating loop so the system can move with more autonomy without losing precision or human control.
Demiourgos
OrchestratorThe delta core decides when models should reason, when tools should act, what memory to load, and when a human should verify the move.