Supercharge your AI coding agents

Deep code awareness through semantic indexing of code, git history, and documentation. Reduce token costs, lower latency, and generate code that fits your codebase perfectly.

Power Your AI Agents

Understand Your Codebase Deeply

Code is indexed to understand structure, patterns, and relationships beyond keyword matching. Agents grasp the bigger picture and make smarter decisions.

Save Tokens, Save Time, Scale Smarter

Efficient indexing and retrieval dramatically reduces token consumption and latency compared to raw agent read operations, especially on large repositories. Save money at scale.

Learn from Every Commit

Indexes git history and commits to understand how code evolved, why changes were made, and historical context. Your agent learns from the past.

Generate Code That Feels Handcrafted

Guides agents to follow existing coding conventions, use appropriate APIs, match architectural patterns, and understand domain context. Code that fits like it was handcrafted.

Comparison

Capability Agent Agent Powered By EmbArk
Large repository Slow grep/search, high latency Fast semantic search, sub-second latency
Token consumption High - repeatedly reads entire files/folders Dramatically reduced via efficient indexing
Code history understanding Can traverse git, but slow and expensive Pre-indexed git history with evolution context
Code search quality Keyword-based (grep, regex) Semantic understanding of code structure
Code generation quality May not match existing patterns Follows conventions, APIs, and architecture
Documentation awareness Manual file reading Integrated READMEs and docs in context

Performance Impact

EmbArk supports...

👥
50K
Monthly Active Users
📦
100K
Indexed Repos
400
Requests per Second
💼
5
Enterprise Customers

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