Open Source AI Tools
We build tools for AI development workflows. Two of them — Orunla and CGC — are free and open source. They were built to solve real problems we encountered while developing our AI SEO platform.
These are developer tools, not part of our agency services. We open-sourced them because they're useful to anyone working with AI coding assistants and we believe the AI developer community benefits from more open tooling.
Orunla
Persistent AI Memory System
Orunla gives AI coding assistants persistent memory across sessions. AI agents like Claude Code, Cursor, and ChatGPT forget everything between conversations. Orunla provides a knowledge graph that remembers facts, relationships, and context — so your AI can pick up where it left off.
Key Features
- Local-first knowledge graph with SQLite storage
- MCP (Model Context Protocol) server for Claude Code and Cursor integration
- CLI tool for terminal-based usage
- REST API for custom integrations
- Temporal decay — memories fade naturally if not accessed
- On-device ONNX-based embeddings (no external API calls for semantic search)
- Built in Rust for speed and low resource usage
How We Use It
We use Orunla in every AI-assisted development session. It stores project architecture, decisions, debugging insights, and user preferences. When we start a new session, the AI already knows the project context. It's the tool that makes our own AI development workflow efficient.
CGC
Context Graph Connector
CGC connects AI agents to your data — files, databases, spreadsheets — without burning through context window tokens. Instead of dumping entire files into the AI's context, CGC maps the data structure first, lets you sample selectively, and chunks large files into manageable pieces.
Key Features
- Multi-source data connectivity (filesystem, databases, spreadsheets)
- Schema discovery and structural mapping
- Smart chunking for large files
- Data sampling without full reads
- MCP server for Claude Code and Cursor integration
- Session management for tracking work across conversations
- Search within data sources without loading full content
How We Use It
CGC is how we keep AI development context-efficient. When exploring a new codebase or data set, we use CGC to discover the structure, sample key files, and only pull in the specific sections we need. It reduces context window waste significantly, leading to better AI responses with less token usage.
Open Source and Our Agency Work
Orunla and CGC are developer tools, not part of our AI SEO services for agencies. Our agency work uses a separate set of proprietary tools (BotSight, the query generator, the multi-platform scraper, and the GEO Knowledge Base) that are purpose-built for AI search optimization.
We open-source what benefits the broader developer community. We keep proprietary what gives our agency clients a competitive advantage.
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