Why evaluation comes before the agent: how we measure what "good" looks like when it comes to AI for product intelligence, and how we meet your organization wherever you are in the transformation journey.
How the Rapidflare agent harness has evolved across four generations — from a simple RAG pipeline in 2023 to a long-running, broader, deeper harness in 2026.
Part II of the Rapidflare Fire Shield series — WAF, reCAPTCHA, edge controls, human review, monitoring, and external pen-test layers around our AI pipeline.
Part I of the Rapidflare Fire Shield series — the multi-layer AI safety filter that classifies every inbound message before retrieval and answer generation.
Agents have a search problem across the whole stack: web search, RAG, tool discovery, skills/workflow loading, and even context compaction.
How Rapidflare engineered LLM-powered autocomplete for AI agents, delivering suggestions in under 300ms with three-layer personalization.
Rapidflare introduces the electronics industry’s first visual-reasoning AI agent, turning schematics, diagrams, and technical visuals into searchable knowledge with diagram-grounded answers for engineering, support, sales, and marketing teams.
Rapidflare Agents now support inline citations, enabling traceable, verifiable AI answers grounded in datasheets, manuals, and standards documents. Built for technical industries where accuracy and compliance matter.
Rapidflare’s native Discord integration helps DevRel teams support large developer communities with accurate, AI-powered responses.
In technical sales, precision and clarity form the basis of trust. Realizing those values in AI agents means building on structured expertise, explainable reasoning, and continuous validation, ensuring accuracy and reliability where every detail matters.
Discover why task-specific AI outperforms generic LLMs in precision, reliability, and context for mission-critical industries.
