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Ship AI agents you can trust

Fidian verifies every decision your agent makes against your spec, in development and in production.

Ahmad Beirami · Co-founder / CEO

The Register: Cursor AI's own support bot hallucinated its usage policy

Reuters: Fallout grows for former law partner sanctioned over AI hallucination

The Guardian: Air Canada ordered to pay customer who was misled by airline's chatbot

AI agents can't be trusted in the real world without verification.

AI agents must align meticulously with business policies and specifications (specs).
Fully defining and verifying these specs at scale is hard.

This is today

Building an agent currently means trial-and-error harness engineering

Specs

Specs matter most, yet today they live unenforced outside the system.

↓

Evals

Evaluations keep going stale the moment your policies or product change.

↓

Harness engineering Everyone operates here

You are tuning prompts, tools, memory, and orchestration code with no reliable signal.

Value lives at the top of the ladder, yet all the labor is happening at the bottom.

Our vision

Nobody will touch the harness; everybody will maintain the specs

Specs You own this

The living source everything downstream will compile from.

↓Evals will regenerate when specs change

Evals You operate here

Compiled from your spec; Fidian will expand edge-case and adversarial coverage.

↓Every harness change will be verified against evals

Harness learning Automated by Fidian

Prompts, tools, and orchestration will evolve against your evals.

You will work only at the top, while Fidian’s automation absorbs the bottom.

Anatomy of an eval

You define what correct means;
Fidian automates the evaluation machinery

Your spec

What correct means for your product globally, covering policies and shape.

You own this

↓

Eval

Scenario

The situation the agent must handle.

Discovered by Fidian

×

Environment

The systems and world state it runs in.

You build and manage this

+

Rubric

Your spec applied to this scenario as pass/fail criteria.

Compiled by Fidian

+

Verifier

Takes the rubric and asserts whether the agent passed.

Automated by Fidian

The future of development

Trust every evaluation signal
by building reliable verification first

1 · Verifiers

Frontier-level accuracy at a tenth of the cost.

Available today

2 · Maintainable evals

Your evaluations regenerate from your specification, so they stop rotting as your product evolves.

3 · Harness learning

Your harness improves automatically against those evaluations without overfitting. The optimized harness is distilled into a new model, and the loop continues.

Fidian self-evolving agents platform

You maintain the spec; the platform evolves evals and the harness.

Why verification first

Flawed verification
doesn’t reveal true agent rankings

Optimizing against a flawed verifier teaches gaming; a worse agent outscores a better one.

Harvey LAB (Harvey’s public legal-agent benchmark) · 1,251 tasks · all-pass scoring (all criteria must pass) · simulated error sweep

Verifier error ε

ε = 0% · verifier accuracy = 100%

Perfect agent (true 100%) Bad agent (true 20%) true all-pass rate

Measured results

We reached near-ceiling accuracy
at a fraction of the cost

Verifiers measured against silver labels (frontier consensus) on Harvey LAB.

Verifier quality: share of real failures caught vs share of correct work accepted

Verifier cost per 1,000 criteria (USD)

More accurate than the default per-criterion grading at about a tenth of the cost.

Fidian is creating a new category of autonomous AI engineering

Fidian provides verifiers tailored to your product’s specifications that run automatically

TAILOREDBuilt from your specifications

GENERICOff-the-shelf correctness checks

LOW AUTOMATIONEvals written and run manually

HIGH AUTOMATIONEvals run and update automatically

Fidian is already in production today

We provide scalable infrastructure for building, deploying, and monitoring reliable AI agents in highly regulated industries

Across pilots, agents reach production 10-20x faster and at a lower cost.

Top 7 Canadian Bank

Deployed AI Advisor for a highly complex lending product

8xconversion uplift

14:1$70K LTV vs $5K CAC

$84Mprojected profit uplift (Year 1)

Leading Network Operations Platform

Deployed a support agent for complex enterprise networks

Pioneering Decentralized AGI Protocol

Built a deep research agent for crypto markets

Demo

An AI life insurance advisor, hardened and verified by Fidian

https://vimeo.com/1203212328/7d2b9d0f05

Venn: integrated problem solving, support from our AI engineering team, product design based on your needs; Fidian at the intersection

We partner with you to solve your team's biggest issues

The pilot phase moves your POC to production while Fidian tunes its verifiers to your domain

Co-founders

The founders led research at frontier labs and scaled enterprise AI.

Ahmad Beirami

CEO/Co-founder

Ahmad Beirami is an award-winning AI technologist and former Research Leader at Google DeepMind, Meta, and Electronic Arts. With an academic background spanning MIT, Harvard, and Georgia Tech, he has over 15 years of experience building highly scalable AI products. He specializes in large language models and reinforcement learning, driving key advancements in systems like Gemini and Meta's digital assistants.

Ali Parandeh

CTO/Co-founder

Ali Parandeh Gheibi is an AI and cybersecurity expert with over 13 years of experience building robust enterprise platforms. With a PhD from MIT, he has held key engineering leadership roles at Palo Alto Networks and Tetration Analytics. Holding over 40 patents, he specializes in 0-to-1 environments, seamlessly blending systems architecture and machine learning to build production-grade AI applications and advanced agentic systems.

< Date >

< Customer >

Your agents are already making decisions.

The question is whether you can stand behind every single one.

With Fidian, you can.

Appendix

The product today

How Fidian works: build it right, keep it right

Two phases. Verification of every change and decision continues.

P H A S E 1

Development

Get it right before anyone sees it.

01

Fidian observes your agent running and maps how it actually behaves.

02

Generates the edge cases and adversarial tests that matter, at scale.

03

Verifies each change against your spec and feeds failures back into the harness.

➜

P H A S E 2

Production

Keep it right as the world changes.

01

Monitors every decision your agent makes in production, in real time.

02

Detects drift the moment the agent starts behaving differently than specified.

03

Keeps the agent reliable as real-world edge cases emerge.

Appendix

We have deep expertise in
frontier model research & enterprise AI

Fidian is a research-driven product company with decades of combined experience building/shipping AI.

Gemini model alignment via controlled decoding and InfAlign; 2x inference speedups via speculative decoding

Led cross-org prototype of first tool-using LLM agent (2020); responsible AI research, adversarial evaluation, red teaming

A decade-plus of AI/ML engineering building production-scale ML systems

Delivered first RL-driven play testing (bug discovery, balance tuning) plus production ML engineering

Architected AIOps for NGFW (now Strata Cloud Management); 30+ years backend systems, SRE leadership

First enterprise-grade data pipelines, ML-driven dependency mapping, regression frameworks

Educational background (PhD)

Appendix

Founding technical team

The technical team has built and deployed autonomous AI systems in production.

Reza Pourabolghasem, PhD

Apple, Electronic Arts

10+ years AI/ML engineering

Specialty

Production-scale ML systems

Hubert Chen

Palo Alto Networks

30+ years backend systems, DevOps

Specialty

SRE, infrastructure engineering

Ninareh Mehrabi, PhD

Meta Superintelligence Labs, Amazon AGI

Responsible AI research at Amazon and Meta

Specialty

Adversarial evaluation, red teaming

Appendix

We believe the future is agentic

Autonomous agents will take over many business functions,
transforming the nature of work, the economy, and society

Today

Teams are deploying AI agents to build and maintain software autonomously

Tomorrow

Complex autonomous systems build agents, make decisions, and transact with each other

Appendix

Today, most teams struggle
to ship reliable agents

Integrity issues will shrink over time as foundational models improve.
The lasting barrier is agent behavior that is not fully specified.

Proof of concept Production

Appendix

We are building infrastructure
that defines agent behavior

Fidian runs your agent live in your environment and drafts verifiable specifications that you own, edit, and approve

Harness

Orchestration

Tools & skills API

Memory management

Verification

Spec evals

Reliability evals

Security evals

Observability and monitoring

Telemetry & traces

Performance & cost metrics

Foundation / infrastructure

Compute (CPU/GPU)

Core models (LLMs)

Storage & DBs

Appendix

You can ship agentic products faster, with more confidence

Fidian empowers your team to meet complex production standards, see ROI, and continually refine your product

Three pillars converge into a base: superior product definition; live, versioned specs evolve with your code

Ship AI agents you can trust

Building an agent currently means trial-and-error harness engineering

Nobody will touch the harness; everybody will maintain the specs

You define what correct means;Fidian automates the evaluation machinery

Trust every evaluation signalby building reliable verification first

Flawed verificationdoesn’t reveal true agent rankings

We reached near-ceiling accuracyat a fraction of the cost

Fidian is creating a new category of autonomous AI engineering

Fidian is already in production today

Demo

We partner with you to solve your team's biggest issues

Co-founders

How Fidian works: build it right, keep it right

Development

Production

We have deep expertise infrontier model research & enterprise AI

Founding technical team

We believe the future is agentic

Today, most teams struggleto ship reliable agents

We are building infrastructurethat defines agent behavior

You can ship agentic products faster, with more confidence

You define what correct means;
Fidian automates the evaluation machinery

Trust every evaluation signal
by building reliable verification first

Flawed verification
doesn’t reveal true agent rankings

We reached near-ceiling accuracy
at a fraction of the cost

We have deep expertise in
frontier model research & enterprise AI

Today, most teams struggle
to ship reliable agents

We are building infrastructure
that defines agent behavior