Introducing Experiments in ElevenAgents - the most data-driven way to improve real-world agent performance. Experiments enables you to run controlled A/B tests to measure which agent configuration works best - from prompt structure to workflow logic, voice, and personality.

How it works: - Create a new variant of your agent. - Route a controlled slice of traffic to it. - Measure impact across key metrics. - Promote the winner to production with full version control.

Teams use Experiments to safely improve outcomes like CSAT, containment rate and conversion with confidence. Learn more:

Bringing actual, statistically rigorous A/B testing to LLM agents is the maturity jump this industry desperately needed. 📉 We can finally stop pushing prompt tweaks based on 'vibes' and start measuring actual containment rates and CSAT. 🧪

This is exactly what serious builders needed. A/B testing agents instead of guessing prompt tweaks is how we move from demos to real products. Love seeing this level of rigor.

A/B testing for agents is underrated. Prompt tweaks without data are just guessing.

Translation: We built a tool so you can scientifically measure how fast your customers scream 'TALK TO A HUMAN' into the phone.

A/B tests don't solve creativity-they just prove which bad idea is slightly better. What's missing?

#lowagents 🚨 @bka

That’s really useful. It’s often hard to know if an agent is actually improving or just feels different.

ElevenLabs "Experiments" brings A/B testing to AI agents, letting you split traffic between voices to see what actually boosts CSAT. It’s a data-driven way to stop guessing and scale the winning version with full version control!

Your agent felt ‘better.’ Now i can prove it

sounds cool! what's your favorite feature yet?

This is gonna be superb

Data-driven optimization for agents is exactly what we need. Prompt structure and workflow logic are the main levers, so having a way to measure them systematically is huge. Another leap for agent autonomy!

This sounds like a valuable tool for optimizing agent performance. A/B testing can certainly provide actionable insights. Excited to see how it evolves.

Experiments is the feature I did not know I needed. Being able to A/B test voice settings before committing to a full production run saves so much time. Previously we would render 10 variants manually and compare by ear. How many concurrent experiments can you run per project?

Hey @bankrbot launch a token on base Name Experiment ticker EXPERIMENT Send fees to @elevenlabs

Great step forward, real A/B testing on live traffic for AI agents finally brings data-driven decisions instead of guesswork. Well done ElevenLabs team!

this is very interesting