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Hamming AI

Automated AI voice agent testing

Humans make billions of calls/day. We think a majority of these will be handled by AI built by thousands of companies tackling every single vertical. Making these AI voice agents reliable is hard. A small change in prompts, function call definitions, or model providers can cause large changes in LLM outputs. Hamming automates testing for AI voice agents. Our voice agents call your voice agent. An AI drive-through startup uses Hamming to simulate thousands of simultaneous phone calls to achieve 99.99% agent order accuracy. We have a proven track record of helping enterprises win with AI. Sumanyu (CEO) previously helped Citizen (safety app) grow its users by 4X and grew an AI-powered sales program to 100s of millions in revenue/year at Tesla. Marius (CTO) previously ran data infrastructure @ Anduril and was a founding engineer @ Spell (MLOps startup acquired by Reddit).

Jobs at Hamming AI

San Francisco, CA, US
$160K - $220K
1.00% - 2.00%
6+ years
San Francisco, CA, US
$140K - $200K
0.50% - 1.50%
3+ years
San Francisco, CA, US
$140K - $200K
0.50% - 1.50%
3+ years
Hamming AI
Founded:2024
Team Size:2
Location:
Group Partner:Gustaf Alstromer

Active Founders

Sumanyu Sharma, Co-Founder & CEO

Sumanyu is the Co-Founder & CEO @ Hamming. Previously helped Citizen grow its MAU by 4X and helped bootstrap revenue from 0 to millions in ARR in under 6 months. Before that, grew an AI-powered sales program @ Tesla to 100s of millions in revenue/year as a Senior Staff Data Scientist. Published a first-author paper in AI during undergrad. BASc from UWaterloo w/ dean's list.
Sumanyu Sharma
Sumanyu Sharma
Hamming AI

Marius Buleandra, Co-Founder & CTO

Marius is the Co-Founder & CTO @Hamming. Previously Eng Manager for Data Infrastructure @Anduril. Founding engineer @Spell (ML Observability & Infra startup acquired by Reddit). Worked on payments @Square and Windows Kernel Virtualization @Microsoft.
Marius Buleandra
Marius Buleandra
Hamming AI

Company Launches

👋 @Sumanyu Sharma and @Marius Buleandra from @Hamming AI

TLDR: Are you testing your voice agents by hand? We're launching Automated AI voice agent testing to automatically test your voice agents and flag quality issues in development and production.

🌟 Click here to try our free Voice Simulations Demo 🌟

Problem: Making voice agents reliable feels like whack-a-mole

Here's the workflow most teams follow:

  1. Call your voice agent by hand and find bugs. Slow and ad-hoc.
  2. Tweak your voice agents by adding new tools and changing the prompts or models to fix the bugs.
  3. Call again to see if the changes worked.
  4. Detect regressions when users complain of things breaking in production.
  5. Repeat steps 1 to 4 until you get tired.

Calling your voice agent & finding bugs is the slowest & most painful part of the feedback loop. This is what we automate.

Our take: Character AI for voice testing

We create hundreds of characters that simulate how real users interact with your voice agents in real life. For every call, we measure whether our character successfully accomplishes the task (e.g., ordering a vegan burger, canceling next week’s appointment, etc.).

Our automated AI voice agent testing approach is 100x faster, cheaper, and more thorough than manual testing.

Flag errors & Tag calls in production

You can log all call transcripts and traces within Hamming. We actively tag your production calls in real-time, and flag cases the team needs to double-click on. This helps engineering teams quickly prioritize cases they need to fix.

Example tags: human detects that the bot is an AI, a follow-up call is needed, the user requested an urgent appointment, etc.

Test new changes quickly

Simulation-driven development

Let’s imagine you’re building an agent called ‘YC Founder’; we can spin up 100s of VC agents who will try to distract you. You can edit the prompts or models and re-run the simulation to make sure you made progress.

Want to see how you would handle a persistent investor? Try our ‘VC trying to distract founders’ free demo here.

Easily create new characters from call transcripts

When customers complain about a bad call, you can locate the call transcript and create a new character in one click. Make a change to your prompt, and then run the simulations to ensure you addressed the bad call.

Meet the team

Sumanyu previously helped Citizen (safety app; backed by Founders Fund, Sequoia, 8VC) grow its users by 4X and grew an AI-powered sales program to $100s of millions in revenue/year at Tesla.

Marius previously ran data infrastructure @ Anduril, drove user growth at Citizen with Sumanyu and was a founding engineer @ Spell (MLOps startup acquired by Reddit).

Summary

We previously launched Prompt Optimizer and AI Experimentation Tools to automate prompt engineering and make RAG pipelines more robust. In this launch, we show how you can test your voice agents quickly.

Our offer

Personalized characters + 100 free calls. Struggling to make your voice agents reliable? We’ll create personalized characters and call + stress test your system ~100 times for free. Book time with us here.

Questions? Email us here or chat with us here.

Other Company Launches

🚀 Hamming - Make your RAG & AI agents reliable

The only end-to-end AI development platform you need: prompt management, evals, observability
Read Launch ›

🚀 Hamming - Let AI optimize your prompts (free for 7 days)

Automate 90% of manual prompt engineering using our self-improving prompt optimizer.
Read Launch ›