DataFramer Services for regulated industries

Make AI work in your business.

Start with the business priority. We’ll work with your team to understand what’s happening today, what success should look like, and what needs to change or improve.

Discuss a business priority Already have a production workflow? Run an Outcome Diagnostic

YOUR WORKFLOWS & SYSTEMS

We work with what you already have.

Apps & Workflows

Models & Data

Tools & APIs

DATAFRAMER SERVICES

Works with your team to figure out what matters and what to do next.

Understand the priority

Diagnose what matters

Put the right next step in place

DATAFRAMER PLATFORM

Runs the measurement and improvement loop continuously.

Signals & traces

Review & evals

Business outcomes

Continuous improvements

How we meet you

Start with the problem you have today.

Whether you're deciding where AI can help, preparing a prototype to ship, or improving production AI, we can start there.

Before AI

Find where AI is actually worth applying.

We look at how the workflow works today, where time or effort is being lost, and where AI or automation could create meaningful value.

“Where is AI worth applying next? Where can AI or automation create the most value?”

We can help identify and prioritize the strongest opportunities.

Prototype

Figure out what it will take to ship.

We help define what success means, how quality will be measured, where expert review is needed, and what should be instrumented before launch.

“What should this AI improve, and how will we know it works?”

We can help establish the outcomes, quality measures, review process and controls needed for production.

Already live

Optimize business impact and AI quality.

We connect business results back to AI behavior, find recurring problems, bring experts into the right reviews, and improve the process over time.

“How do we keep quality, changes, and expert judgment controlled over time?”

We can help find what is holding performance back and put a better improvement process in place.

Your AI stack stays yours. We help make it measurable, reliable and easier to improve.

Not sure which stage? Let's talk

How we work

Start with the priority, then go deep on the workflow behind it.

Understand

Start with the workflow, the business goal and where the team is stuck.

Diagnose

Look at the workflow, systems, data, AI behavior and current measures to find the gaps that matter.

Put it into practice

Help the team establish the right measurement, quality, review and improvement process, with DataFramer where ongoing measurement is needed.

We can stay involved from diagnosis through implementation and ongoing measurement, depending on what the problem requires.

The team

Who you work with

Our team brings experience building enterprise monitoring products, AI evaluation systems, and production infrastructure across AppDynamics, Salesforce, VMware, LLM alignment research, and DataFramer’s own AI quality work. AI evaluation systems deployed in production at Fortune 500 companies.

Puneet Anand

Founder & CEO

Built enterprise monitoring and user-journey systems at AppDynamics, Salesforce and VMware. Inventor on patents in journey monitoring and business-context data collection, and co-author of Hallucinot.

Focus: Business outcomes, workflow intelligence, enterprise systems

Alex Lyzhov

Head of AI

AI researcher with 1,000+ citations across uncertainty estimation, evaluation and model control. Co-author of Hallucinot and research on post-deployment control of language models.

Focus: Evaluation, correctness, model behavior, expert standards

Gabriel Marrocos

Infrastructure & DevOps

Ex-AWS.

Focus: Enterprise architecture, deployment and infrastructure

Backed by Bessemer Venture Partners and Tidal Ventures. More about the team

From diagnosis to implementation

What comes next depends on what we find. That may mean defining business measures, instrumenting the workflow, setting quality standards, establishing expert review, or putting continuous measurement into DataFramer.

Start with a business priority that matters.

We'll start by understanding what you're trying to improve, how the workflow works today, and where the biggest gaps are.

Discuss a workflow