euclidStart
Euclid — Fig. 00 — Scale N.T.S.
01 / INPUTWhere a request enters

The first axiom: what the system is actually given.

02 / OUTPUTWhere a result ships

What the system was built to produce, on a good day.

⚠ FAILURE POINTWhere most systems break

Silently, in production, long before anyone notices. This is where we start.

Euclid — AI solutions, built on proof

We keep AI systems working, or build the ones that will.

Every engagement starts the same way: trace the system, find where the logic breaks, then construct the fix.

Hover the points in the diagram above to see where systems break.

LangGraph
LiteLLM
Pinecone
Weaviate
PostgreSQL
Rust
CoreML
MLX
Docker
Euclid — Fig. 01 — Scale N.T.S.

Given

01REF. A

Output quality has quietly degraded

Nobody noticed until customers did. There was no alert, because there was nothing watching.

02REF. B

The original developer is gone

The freelancer or agency that built it is unresponsive, or the person who understood it left the company.

03REF. C

Nobody can explain the pipeline

Ask three people what the system does and get three different answers, none of them complete.

04REF. D

Costs crept up with no clear cause

The bill grew. The output didn't get better. Nobody traced why.

Scroll to continue ↓

REF. 1–2Euclid — Fig. 02 — Scale N.T.S.

To construct

Two ways in, depending on what already exists.

If — a system already exists

§01 — Rescue

AI System Rescue & Maintenance

Given a system that has stopped working, produce a system that works, and an account of why.

Learn more →

If — there's no system yet

§02 — Build

AI-Native System Builds

Given a problem with no system yet, construct one designed to be traced, evaluated, and trusted from the start.

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Products

Euclid builds and maintains its own tools, to stay sharp on the same problems clients hire us to solve.

Cascaid

In development

Predictive cascading-failure intelligence for agentic and RAG pipelines. Watches the graph of a running pipeline and flags the component about to take the rest of the system down, before it happens.

LangGraph · LiteLLM · Graph Store · GNN

View project →

LocalForge

Beta

An on-device AI code-review engine that intercepts every git commit. Three layers, Rust regex, CoreML, and a local LLM, entirely on Apple Silicon.

Rust · CoreML · MLX · SwiftUI

View project →

Bernn

Launching Oct 2026

One glance at everything you're burning: cloud infra and AI API spend, consolidated into one mobile dashboard, widget, and alert system.

React Native · Supabase · AWS Cost Explorer

View project →
Euclid — Fig. 03 — Scale N.T.S.

Construction

Every engagement follows the same four steps.

01

Diagnose

Trace the system end to end until we know exactly where the logic breaks or drifts.

02

Construct

Build or rebuild the pipeline from first principles. Every component earns its place.

03

Prove

Verify outcomes against measurable, traceable results. If we can't show you why, it isn't done.

04

Maintain

Keep it working after launch, on-call or on retainer, or hand it back fully understood.

Scroll to continue ↓

REF. R1–R3Euclid — Fig. 04 — Scale N.T.S.

Proof

Why this holds up against the alternatives.

Assumed

A freelancer or agency can disappear once paid.

Actually

Euclid's diagnosis is the first deliverable, documented and yours regardless of what happens next.

Fig. 04b — assumed / actual

Assumed

An in-house hire takes months and leaves with the knowledge.

Actually

An engagement starts in days, and the account of the system stays with your team either way.

Assumed

Most tools trace failures after they happen.

Actually

Cascaid, one of Euclid's own products, is built to flag the failure before it cascades.

REF. Q1–Q3Euclid — Fig. 05 — Scale N.T.S.

Questions

Before you start

  • §1 — The difference
  • §2 — Legacy systems
  • §3 — Scope

Diagnosis comes before any code changes, and it's documented, not just performed. That account is yours whether or not the engagement continues.

That's most of what Rescue engagements are. You do not need the original developer's notes or cooperation. We read the system as it runs.

No. Any AI-native system: agentic pipelines, evaluation harnesses, retrieval systems. If it can silently degrade in production, it's in scope.

Q.E.D.

Start a project

  • Diagnosis first
  • Documented, not performed
  • Yours regardless

Tell us what's going on. We'll tell you what we'd do about it.

Start a project