Coral is the open source data engine for enterprise AI. It repeatedly wins benchmarks as the most token efficient and accurate way for any agent to retrieve data from APIs, databases and internal systems. 

Under the hood, Coral centralises auth, retries, pagination, rate limiting, schema mapping, caching, and cross-source joins, once, for all your agents. And it enables you to define access permissions without giving LLMs direct API credentials with wide scopes.

In practise, that means:
→ More accurate answers from joined context across systems 
→ Lower token waste from fewer multi-step tool calls
→ Better security with fine-grained access control and auditing

We benchmarked Claude Code using Coral in place of MCPs from popular SaaS tools (Datadog, Sentry, Linear, Slack and Github). Across the more complex tasks that typify coding agent data retrieval workloads, Claude was 31% more accurate and 70% more cost efficient with Coral. 

Coral’s core product is Open Source under Apache 2.0 with enterprise support available. You can run Coral from your local machine or a sandbox in your cloud, without data leaving your environment. 

How can more accurate, cost efficient agents help transform your org? 

Start at: https://github.com/withcoral
Contact our Team: https://withcoral.com/contact

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