Dynamic AI
built on a live world model
of your intentions

Grant your apps common sense and domain expertise
Ship high-quality features, no slop, hella fast
Transmute research into gold overnight

What is Apothic AI?

Apothic AI is the infrastructure layer for self-improving apps. We train live world models and evolving agent networks on your product so experiences adapt to users, not the other way around.

You focus on your product. We evolve the intelligence behind it.

Your Sales
Kindra Agent
AI reps for phone, voice & DMs
Your Website
Dyna
Adaptive AI-driven UI
Apothic Ecosystem
Evolutionary agents, tools & memory
sMCP Gateway
Agent-coded tools
Helix
Agent orchestration
YOLO
Coding agents
Dyna
Adaptive UI engine
Adaptive World Model
Live world model, memory & learning
Your Engineers
YOLO
Self-evolving coding agents
Your Business
Director
Adaptive management agent
01 | Developer-first

Skip Months of AI Infrastructure Work

Building multi-agent AI systems normally means weeks of designing architectures, wiring agents, bolting on memory, and wrestling infra. Apothic AI ships that stack for you out of the box—evolving agent networks, tools, world models, memory, and adaptive UI—so your team can ship product instead of scaffolding.

Building from scratch

Design multi-agent architecture
2–3 weeks
Build agent orchestration & messaging
3–4 weeks
Implement memory & state management
4–5 weeks
Integrate models & build scaling infra
3–4 weeks
Testing, hardening & deployment
2–3 weeks
Total time to production
14–19 weeks

With Apothic AI

Define agent goals & capabilities
1–2 hours
Connect your existing APIs & tools
1–2 hours
Configure UI surfaces & workflows
Minutes
Deploy & start agent training
~1 day
Monitor & refine performance
Ongoing
Total time to production
1–2 days
02 | Comprehensive Product Suite

Everything You Need to Build Self-Improving Apps

From evolving specialist agents to dynamic UIs, Apothic AI gives you the building blocks for applications that think, learn, and adapt on their own. Ship production-ready intelligence without rebuilding the agent, memory, or UI stack yourself.

Adaptive Agent Network

Agents that discover which tools and strategies work best for each task, then reuse those patterns across new situations. The system spawns specialists on demand and orchestrates them for you.

Task Orchestrator • Agent Manager • Human Interface

sMCP Gateway

Lets agents code their own tools and MCP workflows on the fly inside secure TypeScript sandboxes and Docker-isolated sessions. Bridge cloud and local MCP servers while keeping full observability and policy control.

Learn more about sMCP

Powerful Tool Suite

Tool chains and model execution are automatically tuned per agent, so they get what they need without you hand-crafting MCP configs or babysitting tools.

Web Tools • Shell Access • sMCP Client • Model Runner

Intelligent World Models

Built-in world models with biologically inspired memory for every agent. The Qualia Plane maintains dynamic, self-consistent worlds so agents keep useful context across sessions and tasks.

Qualia Plane • Agent Memory • World Models

Dynamic User Interfaces

Agents can create, test, and update live UI components that adapt to user behavior in real time—without constant manual front-end rewrites.

Component Library • Auto Testing • Live Updates

Unified Model Access

Seamless integration with leading model providers plus free managed model hosting. Run frontier models through a single unified API—at a fraction of typical provider cost.

Multiple Providers • Unified API • Model Hosting
05 | Latest Posts

Field Notes from the Apothic Lab

Deep dives on world models, agent architectures, and the infrastructure behind self-improving apps - what we're learning as we turn research into product.

No lab notes published yet

We're currently training the Apothic stack. First posts will cover the launch of our alpha.