AI SOFTWARE + AUTONOMOUS SYSTEMS + PHYSICAL COMPUTE

We build
intelligence
into things.

Dime9 Labs develops AI-native SaaS, automated agent flow systems, and a 3D engine for intelligent PCB design—from software that assists people to systems that operate on their own.

Explore the lab See agent systems
200+AI applications
3systems: products / agents / silicon

01 / WHAT WE BUILD

One lab.
Three systems.

Products people use. Agents that execute. Hardware tools that reason in space. We build across the stack where intelligence turns into useful action.

01

AI SaaS Development

Software that does the work.

AI-native applications, vertical SaaS, internal systems and intelligent interfaces designed around useful outcomes—not AI as decoration.

  • Products
  • Vertical SaaS
  • Interfaces
  • Data
02

Automated AI Agent Flow Systems

Systems that keep moving after you leave.

Event-driven and scheduled AI workflows that plan, delegate, call tools, share memory, verify outputs and complete multi-step work with minimal human intervention.

  • Multi-agent
  • Orchestration
  • Tool use
  • Memory
  • Triggers
  • Guardrails
03

AI PCB / 3D Engine

Design space you can think inside.

We are building toward a 3D-native environment where AI can reason about board geometry, components and spatial constraints as part of the design process.

  • 3D-native
  • Geometry
  • Constraints
  • AI-assisted
04

Intelligent Hardware

Silicon with a job to do.

When no off-the-shelf part fits, we design the hardware the application demands—AI-optimized board layouts, custom silicon concepts and co-designed software-to-chip pipelines.

  • Custom silicon
  • Board design
  • Co-design
  • Edge AI

02 / AGENT INFRASTRUCTURE

From prompt
to operating system.

A useful agent is not a chat box with more steps. We build persistent AI operating flows that can observe state, choose work, act through tools and return evidence.

01Observe

Webhooks, schedules, queues, files, messages, databases and system events.

INPUT
02Plan

Intent classification, decomposition, routing, model selection and dynamic task graphs.

REASON
03Act

APIs, browsers, code, internal services, databases and domain-specific tools.

EXECUTE
04Remember

Short-term state, long-term memory, retrieval and shared multi-agent context.

CONTEXT
05Verify

Policy checks, deterministic validation, confidence gates, retries and human escalation.

CONTROL

Single agents when one is enough. Multi-agent systems when specialization creates leverage. Deterministic code around both.

03 / BUILD VELOCITY

Two hundred products changes how you see one.

We have built more than 200 applications. Repetition creates a different kind of product instinct: what matters, what does not, and how little machinery a useful idea actually needs.

04 / THE METHOD

Less stack.
More signal.

  1. 01

    Find the hard part.

    Start with the actual bottleneck, not the feature list. Strip the idea down until the useful mechanism is obvious.

  2. 02

    Build the shortest path.

    Prefer native primitives, small surfaces and direct systems. Complexity has to earn its place.

  3. 03

    Make it compound.

    Every product becomes a reusable lesson, component or capability for the next system.

05 / ENGINEERING TASTE

Performance is part
of the interface.

06 / DIME9 LABS

Software.
Agents.
Silicon.

We build AI products across the stack—from applications people use, to autonomous systems that execute work, to tools that shape the hardware underneath.

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