Evals in Production: Lessons from Building AI Agent Evaluation Frameworks

September 1, 2026
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September 1, 2026
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Drawing on agentic AI deployments across financial services, life sciences, investment management, and technology sectors.

Why This Paper Exists

Most enterprises are not failing at AI because of the technology. They are failing because nobody is measuring whether it works.

This paper is the product of eight real deployments and the kind of operational detail that only comes from having actually shipped AI in production, in banking, pharma, investment management, and beyond.

Metrics Display
8
Enterprise Deployments
$20M
Cost Reduction, Pharma
65%
Faster Delivery, Banking
16x
Faster Drug Discovery
97%
Client Repeat Rate

Inside the paper

  1. The evaluation landscape
    Three phases of production evaluation, output-type complexity, and the closed-loop model.
  2. Case studies in enterprise evaluation
    Proxy voting intelligence, pharma-grade platforms, cybersecurity remediation, NL2SQL, and RBAC-aware RAG.
  3. Tooling decisions and trade-offs
    Build vs. buy analysis, LLM-as-judge strengths and failure modes, and adversarial red teaming.
  4. Emerging principles for enterprise AI evaluation
    Six cross-cutting patterns distilled from all eight engagements.

A Sample evaluation report
Anonymized Agentic AI Evaluation Dashboard covering 5,090 test cases across three platforms.

Industries covered

Financial Services .  Life Sciences and Pharma .  Investment Management . Cybersecurity . B2B Enterprise Software

Who should read it 

Senior leaders past the pilot phase asking harder questions. Why is adoption stalling, where is the value, and what does it take to run AI at enterprise scale in a regulated environment. It assumes technical fluency but does not require it.

Author & Contributors
Author
Shivkumar Krishnan
Contributing Architects and Technical Leads
Martin Gaida
Sathiyanarayanan Gopal
Atharva Joshi
Konrad Jackowski
Sandeep Kalra
Pavan Muthozu
Yasmeen Sultana
Mahesh Varavooru
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Amit singh

“Amit Singh is the Chief Strategy Officer and Chief of Staff to the CEO at Altimetrik, where he drives corporate strategy, growth acceleration, and value creation through transformation initiatives. In this dual role, he partners closely with leadership teams, investors, and the board to align business strategy with sustained, technology-driven growth.

With over two decades of experience at the intersection of technology, business, and transformation, Amit brings a unique perspective on how organizations can innovate and adapt in a rapidly evolving digital landscape. His career has been defined by building high-performing teams, scaling innovative platforms, and driving organizational change to deliver lasting impact.

Before joining Altimetrik, Amit held senior leadership roles at Visa, where he led technology strategy, engineering, and product development for Real-Time Payments and the Visa Developer Platform. Earlier, he served as Chief Product Officer at a startup and spent more than a decade at Oracle, leading product and engineering teams across a wide range of enterprise software applications.”

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