Data-backed insights on the tools top AI teams rely on, across observability, evaluation, deployment, security, analytics, and more.

AI teams are facing accuracy issues, rising evaluation costs, and pressure to deliver production-ready LLMs fast.

This report shows how top organisations are solving those problems right now, and the tools they trust most.

What you’ll get

🔥 The top tools across 9 essential LLMOps categories. Observability, deployment, testing, security, analytics & more.

🔥 What roles actually want. Data scientists need automation, product teams need hybrid evaluation, and business needs interpretability.

🔥 How LLMOps maturity shapes tool choice. From pre-adoption uncertainty to the real bottleneck: human evaluation costs.

🔥 The 3 trends defining 2025. Autonomous ops, cost optimisation, proactive governance.

SPONSORED by Prolific
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Human feedback is becoming the bottleneck. Prolific powers:

  • RLHF
  • Red teaming
  • Evaluation
  • Data generation & annotation

All via a vetted, high-quality participant pool.

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65 pages. Practitioner insights. Actionable frameworks.

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