We benchmarked Avoma’s own MCP server against a task-specific Nexla MCP server on call analysis. Nexla returned exact call counts and direction splits, logged 1 errored tool call to Avoma’s 25, and installed with a service key instead of OAuth.
AI-ready data is governed, semantically described, and pipeline-stable. Get the 2026 definition, a checklist, and the gap from analytics-ready to AI-ready.
What is a scoped MCP server? A scoped MCP server exposes only the specific tools…
Connecting an agent to everything feels like progress. In practice it is the fastest way…
Your best reps already know which deals are slipping. The hard part is that the…
As AI agents reach into enterprise systems, the question is not whether they can connect, but whether they do it without bypassing your security controls. Here is how Nexla keeps MCP access tied to each user’s identity and credentials, and lets your systems keep enforcing their own policies.
The agent didn’t give a wrong answer because the model was weak. It gave a…
Meet Nexie, the AI knowledge agent on nexla.com that answers your hardest questions about agentic data integration, without the sales pitch.
MCP Tool Bench is a controlled way to benchmark MCP server design. We put Nexla’s task-specific MCP servers against off-the-shelf ones on real BigQuery tasks, in two harnesses, and measured the agent effort each demanded.
Raw RAG systems still hallucinate because they lack business context. Learn how semantic abstraction and Nexsets improve AI agent reliability.
Batch data breaks AI agents in production. Real-time context ensures fresh, reliable decisions powered by CDC, streaming, and data products.
A data platform for AI agents must do 7 things: connect, abstract, govern, deliver, act, observe, secure. Use this checklist to evaluate any vendor or stack.
Give AI agents secure access to enterprise data without rebuilding your stack. Compare DIY vs. managed paths, see a 1-week vs. 12-week timeline, pick what fits.
