This isn't AI.
This is EI.
AI coding agents aren't dumb. They're blind. We build the infrastructure that gives them sight — and the gates that force them to use it.
What We Do
Building the infrastructure for AI that actually works in production.
Verification Infrastructure
Six MCP servers that give AI coding agents sight into project history, runtime behavior, API contracts, code quality, security, and web content. Six blindnesses no model improvement will fix.
Local-First Architecture
SQLite + WAL + FTS5. No cloud. No Docker. No external databases. Every tool persists intelligence in a single file next to your code. Install via pip/npm and go.
Enforced Quality Gates
Mutation testing, security scanning, and a dev loop with phase gates that reject empty claims. Agents must submit evidence — a sibling file read, test output, a Seraph grade — before they can advance.
The EvoIntel MCP Suite
Six tools for six blindnesses. Each one gives AI coding agents sight into something no model improvement will ever fix — plus the gates to make sure they actually look.
Sentinel
AI agents are blind to project history. Sentinel mines git for conventions, pitfalls, architectural decisions, hot files, and co-change patterns — institutional memory for your AI.
Niobe
AI agents are blind to runtime behavior. Niobe snapshots process metrics, ingests logs, detects anomalies, and compares before/after states — eyes on the running system.
Merovingian
AI agents are blind to cross-service dependencies. Merovingian maps API contracts, tracks consumer relationships, and detects breaking changes across repository boundaries.
Seraph
AI agents are blind to real code quality. Seraph runs mutation testing, static analysis, security scanning (bandit + semgrep + detect-secrets), flakiness detection, and risk scoring — because 'all tests pass' is not a safety guarantee.
Anno
AI agents are blind to web content. Anno strips 93% of HTML noise so your agent reads clean, structured text — not 15,000 tokens of scripts and ads.
Install and start building
pip install git-sentinel # Project history
pip install niobe # Runtime observation
pip install merovingian # Dependency intelligence
pip install seraph-ai # Verification + security
pip install morpheus-mcp # Protocol enforcement
npm install -g @evointel/anno # Web content extractionAlso Building
Products powered by the EvoIntel stack.
Zado
ADHD-friendly budgeting with AI coaching. Five distinct coach personalities adapt to your financial style, with real bank account sync via Plaid.
EIF
Ethical Intelligence Framework for medical device AI validation. Automates the compliance process that typically takes teams months of manual review.
How We Build
We don't build isolated tools. We build interconnected systems where every component makes the others smarter, safer, and more capable.
Tools That Compound
Every tool strengthens the others. Sentinel's pitfall history feeds Seraph's risk scoring. Seraph's grades feed back into Sentinel's confidence scores. Morpheus orchestrates all of them and saves what it learns for next time. The stack compounds — every session makes the next one better.
Intelligence That Persists
AI agents forget everything between sessions. Ours don't. Sentinel saves what the agent learns — patterns, pitfalls, fixes — and surfaces them next time. Error fingerprints match across files and sessions. Knowledge accumulates instead of resetting to zero.
Enforcement, Not Guidelines
We caught our own AI agent rubber-stamping quality checks — claiming it read a sibling file without actually reading one. The fix wasn't a better prompt. It was Morpheus: phase gates with evidence requirements. The agent must prove it checked before it can advance. Same reason CI pipelines exist.
The Builder
Evolving Intelligence is built by Nicholas Smith — an AI engineer and ServiceNow developer who ships production systems. Six MCP servers published to PyPI and npm. 900+ tests. All open source.
The thesis: AI coding agents fail not because they're dumb, but because they're blind to things no model improvement will fix — project history, runtime behavior, cross-service dependencies, real code quality, and web content noise. The EvoIntel stack gives them sight and the gates to prove they used it.
Read the full argument in the white paper — including how the stack independently converges with Anthropic's published research on agentic coding challenges.
Let's build something that matters.
Whether you need AI infrastructure, ethical frameworks, or a technical co-builder — let's talk.