Zenbase helps developers focus on programming by automating prompt engineering and model selection.

We’re core contributors of Stanford NLP’s DSPy, the #1 LLM optimization framework used by Meta, Microsoft, Google, among many others. But it's hard to use outside of academia.

We're building the production version.
Continuous prompt optimization for LLMs from DSPy core contributors
Title: Zenbase AI: Continuous prompt optimization for LLMs from DSPy core contributors | Y Combinator

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### Continuous prompt optimization for LLMs from DSPy core contributors

Zenbase helps developers focus on programming by automating prompt engineering and model selection. We’re core contributors of Stanford NLP’s DSPy, the #1 LLM optimization framework used by Meta, Microsoft, Google, among many others. But it's hard to use outside of academia. We're building the production version.



Zenbase AI

Founded:2024

Team Size:2

Location:San Francisco

### Active Founders

### Cyrus Nouroozi, Founder & CEO

Cyrus is the Co-Founder @ Zenbase AI and a core contributor to Stanford NLP's DSPy. He went from 0 to PhD-level AI researcher in 4 months in 2023, and taught himself how to code when he was 14. He enjoys the little moments in a day with coffee, ecstatic dance, and tai chi.



### Amir Mehr, Co-Founder & CTO

With a Master’s in Computer Science from the University of Calgary and as a key contributor to StanfordNLP's DSPy project, Amir has deep expertise in AI and software engineering. He played a crucial role in engineering at HubMeta and OVOU. His early success running a profitable web hosting business in high school showcases his technical acumen and entrepreneurial drive.



### Company Launches

[### Zenbase: Continuous prompt optimization from DSPy core contributors](

**TL;DR:** Zenbase helps developers focus on programming by automating prompt engineering and model selection. We’re building developer tools and cloud infrastructure for teams to save time, never get stuck in prompt hell, and create AI apps that get smarter over time.

Hey there! We're [Cyrus]( & [Amir]( In the past, we've both been lead engineers and founding CTOs. We became contributors to [DSPy]( and discovered the future of programming with language models.

This is the story of how we came to this insight, our glimpse into the future, and 2 case studies on how Zenbase has helped companies escape prompt hell and scale prompt engineering.



Problem
-------

Prompt “engineering” is the most time-consuming, stressful, and uncertain part of programming with LLMs. With DSPy, we had found something profound. It promised to save us from the all-too familiar user journey we — like so many others — had experienced.



DSPy kept growing. It became Stanford NLP's #1 GitHub repo with 16K stars. We started hearing of folks in Microsoft, Amazon, Google, and 40+ other companies using DSPy to prototype apps with it.

We began hearing the same things all over again. Although many found DSPy elegant and intuitive, countless folks found it impossible to grok. Those who managed to build something with it had headaches productionizing it; finding it difficult to scale, make reliable, and make performant.

So, we set out to create the productionized DSPy.

Solution
--------



Zenbase lets you optimize your prompts and models. We offer:

1.  [zenbase/core]( is an open-source Python library that you can use to optimize your existing LLM pipelines using DSPy’s optimizers (versus having to rewrite your pipelines in DSPy)
    
2.  A hosted API for creating AI functions that get smarter with time. We ingest user feedback to continuously optimize the prompt and model.
    
    We use the latest tricks from DSPy, our own custom optimizers, and fine-tuning as appropriate to execute your intents in a way that's good, fast, and at a reasonable price.
    
3.  An on-prem API for businesses with data privacy requirements.
    

Use Cases
---------

### How Zenbase saved Vera from Prompt Hell

> **Zenbase came into the trenches with us to improve our evals from 10% to 80%.** It really felt like they were a part of our team.
> 
> — Taeib, Cofounder @ [Vera-Health.ai (YC S24)](

They were staying up until 3am on multiple nights trying to prompt engineer their RAG query generator to retrieve the correct documents. Their progress was uncertain. It was stressful. We call this prompt hell.

Prompt engineering is the most uncertain, risky, and stressful part of programming with LLMs. There didn’t seem to be a way out, but with Zenbase, they saw the light at the end of the tunnel.

Zenbase makes prompting systematic and peaceful. **We helped Vera go from demo to production, by optimizing the prompt of their query generator.** With a product that could handle doctors’ stress tests, they could focus on selling, and go to bed at a good time.



### How Zenbase helped Superfilter create an AI that’s personalized to its users

> I’ve seen a lot of AI Devtools and Zenbase is solving a problem that everyone building with AI will have when going to production. **The best part is their product is so easy to use that it’s a no brainer.**
> 
> — Scott, CEO @ [Superfilter.ai]( (YC S24)

It was all going great. Superfilter had just tested their AI email copilot with their beta users of investors and startup founders, and their users were excited. They onboarded a new cohort, and their prompts broke down. It worked well for the investors and startup founders, but not everyone.

Scott and his cofounder Travis realized that prompt engineering wasn’t going to scale to accurately categorize user emails into important, action required, or ignore.



Superfilter used our hosted API to create email categorizers that learned from users’ existing behaviour. With automatic prompt engineering, they were able to scale personalized experiences for every user.

**Zenbase makes personalized AI apps easier to build and scale with automated prompt engineering.**



Asks
----

1.  Are you in prompt hell, and do you want to feel the Zen? Are you trying to scale the personalization of prompts for every account?Learn more [on our website]( and [schedule a demo]( with us so we can understand where you are and where you want to be. Let us be your LLM doctors and wizards as we guide you to where you want to go.
    
2.  Use our [MIT-licensed Python SDK]( to optimize your existing prompts with DSPy’s optimizers.
3.  Kindly share this post with anyone you know who could benefit 🙏

### Hear from the founders

#### How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)

Cyrus and Amir have been working in startups as lead engineers and CTOs for 10+ years.Cyrus and Amir were introduced by a mutual friend 3 years ago. Worked on a handful of consulting projects together. Cyrus would sell, Amir would build. They were building AI apps and wondered, what if there were a way to use AI to write the prompt. Then, Cyrus discovered [DSPy]( the home of automated prompt engineering. He met up with its creator and took on a major role in the project. He persuaded Amir to join in. They became core contributors.Being startup guys at heart, they started exploring opportunities, and things just started clicking into place.

#### What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?

AI systems are static prompts and models. AI systems need to be able to learn on the job. We build AI systems that can learn.

#### What is your long-term vision? If you truly succeed, what will be different about the world?

**Developers save time and effort:** With Zenbase, they can ship high quality AI features in hours and not days.**Users receive a better product:** They can confidently delegate knowledge tasks with more because they have an AI that gets smarter and faster the more you teach it.**Businesses drive quality and margins:** The highest performing, most cost-effective prompt and model for the task are always used.
