Better Architecture. Better Models. Lower Cost.

Open-source LLMs, structured delegation pipelines, and defined workflows.

What we build

Simple, useful AI systems. Not a giant transformation plan. Start with one painful workflow and make it better.

Internal AI assistants

Help your team answer questions, draft documents, research, summarize, and make decisions using your actual business context.

Workflow automation

Connect AI to email, CRM, spreadsheets, calendars, databases, and APIs so repetitive work happens faster with fewer handoffs.

Customer-facing agents

Website, SMS, email, or chat agents that answer questions, qualify leads, route requests, and escalate when a human is needed.

How it works

Start small. Ship fast.

The goal is not to overwhelm your company with AI. The goal is to find one place where AI can save time, reduce errors, or create a better customer experience.

1

Tell us the workflow that wastes time or causes mistakes.

2

We build a focused working version with the tools you already use.

3

Your team tests it in real work, then we improve from there.

Not sure if AI fits your workflow?

Send one process that's repetitive, error-prone, or expensive to run. We'll tell you honestly whether AI belongs there — and what a working version would look like if it does.

Architecture

Architecture.

Open-source models are only the starting point. The advantage comes from routing, delegation, defined workflows, integrations, and auditable output — built as one system.

1

Best-Fit Models

Choose the right tool for each job

Every task uses the model best suited to it — optimized for accuracy, speed, and cost. No single-vendor lock-in, no paying for capability you don’ need.

input
2

Model Router

Task-aware orchestration

Intelligent routing directs queries to the most capable model based on complexity, latency, and cost requirements.

route
3

Structured Delegation

Specialist agents by role

Complex tasks decomposed into subtasks handled by specialized sub-agents with focused capabilities.

delegate
4

Clear Process

Built around the work

The workflow is clear, practical, and easy for your team to review and improve as the work changes.

process
5

Tool Integrations

APIs, databases, docs, CRMs

Native connectors to the tools your team already uses — no rip-and-replace required.

connect
6

Auditable Output

Logs, reviews, ownership

Every decision and output is logged, traceable, and reviewable — built for compliance and continuous improvement.

verify

Open-Source Landscape

What we actually run

The open-source stack we recommend — because we run it in production. Inference, self-hosted models, and the agent layer, with the hardware and the reasoning.

Inference

Makora

Agentic kernel + inference generation

Where to run the hot path when speed is the product.

Makora generates and fuses GPU kernels from plain code — the same engine behind our 0.013 ms field-report kernel. If your workload has a measurable hot path, Makora turns it into native CUDA instead of paying for an opaque hosted endpoint.

makora.com

Self-hosted models

DeepSeek V4 Flash

Self-hosted on 2× RTX PRO 6000

Where to run a frontier-class model with zero per-query cost.

A frontier-class small model you can run on hardware you own — in this case two RTX PRO 6000 cards. Same class of model we benchmarked at 0.950 on the production gate, with data never leaving the building and no per-query fees.

huggingface.co

Agents

Prime · Pi · ZCode Desktop

The agent stack we actually run

Where to put the orchestration, coding, and resident workers.

Prime for hosted training and verifiers, the Pi coding-agent SDK for long-running resident agents, and ZCode Desktop as the daily coding surface. This is the stack running this site, our field reports, and the production systems behind them.

primeintellect.ai