MCP Tool Bench is a controlled way to benchmark MCP server design. We put Nexla’s task-shaped MCP servers against off-the-shelf ones on real BigQuery tasks, in two harnesses, and measured the agent effort each demanded.
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.
Agentic RAG replaces static retrieval with planning, tool use, and reflection. See the architecture, when to choose it over RAG, and metrics that actually matter.
MCP for enterprise data turns 600+ source systems into tools agents can compose. Compare build vs. buy, governance models, and a 12-week deployment plan.
Data for AI agents needs governance, lineage, and continuous freshness. Learn the 7-pillar readiness model and a 90-day rollout plan to ship agent-ready data.
Learn how to automate F5Bot alerts into Slack using Nexla to track Reddit and Hacker News mentions in real time.
Today, we’re super-excited to bring a major design update to the Nexla UI! Using our…
Operationalizing Large Language Models (LLMs) is the next big opportunity in AI. Any organization…
Challenge Databricks is a cloud data platform built to store, process, and analyze big data…
Challenge When data is collected from a variety of sources, it arrives in different formats,…
Challenge Zendesk Suite is an emerging favorite for many companies this year as it provides…
