AI Evaluations

AI Agents

Future AGI October Roundup

Future AGI October Roundup

Future AGI October Roundup

Future AGI October Roundup

Future AGI October Roundup

Future AGI October Roundup

Future AGI October Roundup

Last Updated

Oct 31, 2025

Oct 31, 2025

Oct 31, 2025

Oct 31, 2025

Oct 31, 2025

Oct 31, 2025

Oct 31, 2025

Oct 31, 2025

By

Rishav Hada
Rishav Hada
Rishav Hada

Time to read

1 min read

Table of Contents

TABLE OF CONTENTS

🚀 Product Updates

Open-Source Stack for AI Reliability

 { Simulate → Evaluate → Optimize → Observe → Protect}

We are excited to open-source Future AGI’s complete AI agent reliability stack trusted by 250+ enterprise and startup teams shipping production AI. 

Building agents is easy but keeping them reliable in production isn't. Evals crash under load, tests don't scale, guardrails kill latency, traces scatter everywhere. Our open-source stack solves this-

  • Simulate SDK: Test voice agents at scale with realistic customer simulations, cutting cost by 70%

  • AI Evaluation: 60+ multimodal evals + custom metrics that don't crash on real workloads

  • Agent-Opt: Auto-optimize agents and prompts with battle-tested algorithms

  • traceAI: Unified observability across all LLM providers and frameworks

  • Protect: Multi-modal guardrails that actually work (97.2% accuracy, sub-65ms)

pip install agent-simulate ai-evaluation agent-opt traceai

Enterprise-grade reliability without the enterprise tax. Built for teams shipping AI systems that can't afford to fail.

Quick start docs | GitHub | Try free

Future AGI + Vapi: Complete End-to-End Stack for Voice AI

We're bringing the complete simulate-evaluate-observe stack to Vapi's voice AI platform. Vapi handles your voice infrastructure - ASR, LLM orchestration, and TTS at scale. 

Future AGI adds the intelligence layer on top: simulate thousands of edge cases before deployment, run production-grade evals on voice interactions, and monitor everything in real-time with unified traces across your entire stack.

Production insights automatically convert into test cases, so your agents improve with every deployment. This integration gives you complete visibility without the complexity.

Available now for all Vapi users.

👉 Setup observability for your voice agent. 

Targeted Scenario Testing - Run What Matters

Re-run specific test scenarios or evaluations without restarting the entire simulation for your voice agent. Target edge cases precisely, reduce evaluation costs, and iterate faster on failing tests. Perfect for fine-tuning edge cases and debugging specific workflow branches without burning through time, compute, and credits. 

Test specific agent scenarios ->


🌐 Knowledge Nuggets

Free eBook - Agentic RAG for Enterprises

Around 90% of RAG implementations fail in production because teams move directly from theory to deployment without a validated framework. Our playbook provides proven guidance on chunking strategies, implementation methodology, hallucination prevention, ROI optimization, and other best practices used by successful teams at scale.

🔗 Get your free copy here

Webinar on ‘Building Auto-Optimizing Agents’

Watch a live demo on how to build self-optimizing AI agents that evaluate, learn, and improve automatically. See how eval-driven loops replace manual tweaking with continuous performance gains, no human in the loop.

Learn how to automate testing, shrink optimization cycles, and ship smarter agents faster.

🔗 Watch or save for later - click here!

We were at VAPICON 2025

We showcased SIMULATE, stress-tested voice agents live, and captured plenty of ‘WOW’ moments while connecting with founders, researchers, and builders in the Voice AI community. Huge thanks to everyone who stopped by our booth and to our event squad - Nikhil, Charu, and Vrinda!

Tech Disrupt 2025

TechCrunch Disrupt - it exceeded every expectation. Three days of back-to-back conversations with founders and engineers who are done chasing hype and ready to solve real problems, how to measure reliability, optimize agents in production, and catch issues before customers do. We had close to 500 people stop by, and every conversation felt like it mattered. The vibe was different this year. Less "look at my cool demo," more "let's figure this out together." That's exactly the shift we've been waiting for.

November is here, and AI is leveling up faster than ever.

Facing tricky AI problems? Slide into our DMs and share the challenges you’re tackling, let’s brainstorm solutions together.

🗓️ Book a free demo or schedule a call to see our platform in action!

Your partner in building Trustworthy AI!

Table of Contents

Table of Contents

Table of Contents

Rishav Hada is an Applied Scientist at Future AGI, specializing in AI evaluation and observability. Previously at Microsoft Research, he built frameworks for generative AI evaluation and multilingual language technologies. His research, funded by Twitter and Meta, has been published in top AI conferences and earned the Best Paper Award at FAccT’24.

Rishav Hada is an Applied Scientist at Future AGI, specializing in AI evaluation and observability. Previously at Microsoft Research, he built frameworks for generative AI evaluation and multilingual language technologies. His research, funded by Twitter and Meta, has been published in top AI conferences and earned the Best Paper Award at FAccT’24.

Rishav Hada is an Applied Scientist at Future AGI, specializing in AI evaluation and observability. Previously at Microsoft Research, he built frameworks for generative AI evaluation and multilingual language technologies. His research, funded by Twitter and Meta, has been published in top AI conferences and earned the Best Paper Award at FAccT’24.

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