ABOUT

Ariana Abramson

Founder, CosentriQ. Building AI Model Behavior Evaluation & Human Validation.

I'm a second-time founder building the human-side evaluation layer for AI.

My work sits at the intersection of computer science, information systems, product strategy, and responsible AI.

I hold a Master's degree from Columbia University and a background in Computer Science — a combination that shaped how I think about AI systems not only as technical products, but as interconnected layers of model behavior, product design, human judgment, and real-world consequences.

That perspective has defined my career.

Before CosentriQ, I founded DivySci, an AI and data technology company that grew from $0 to more than $4 million in annual recurring revenue.

During that journey, I experienced firsthand what happens when an AI product reaches the market without a reliable system for evaluating how its behavior affects the people using it.

Technical performance can look strong while users remain confused, place too much or too little trust in an output, or fail to take the action the product was designed to support.

That gap between technical confidence and real human response became the foundation for CosentriQ.

CosentriQ — AI Model Behavior Evaluation & Human Validation

CosentriQ helps AI teams evaluate and improve how their products behave with real users.

The platform combines agentic simulation with structured human validation to identify behavioral risks, measure the gap between predicted and observed user response, and turn those findings into clear recommendations across prompts, outputs, guardrails, workflows, and escalation paths.

CosentriQ also generates the governance documentation teams need to define expected behavior, track risks, and preserve evaluation decisions as their products evolve.

We support fast-moving teams building AI assistants, copilots, agents, and decision-support products from pilot to production.

Claim a Free CosentriQ Launch Seat →

The Human Evaluation Network

CosentriQ's structured human validation layer is powered by DollarFifteen, a paid contributor network designed to bring broader human judgment, context, and lived experience into the evaluation of AI systems.

I believe human-in-the-loop must evolve into community-in-the-loop: the people affected by AI should have a meaningful role in evaluating how those systems behave.

This work did not come from theory alone.

It came from building, scaling, failing, studying the gap, and choosing to create the system I wish had existed when I needed it.

Build AI that behaves reliably, acts safely, and earns users' trust.

Education

  • Columbia University Master's in Information & Knowledge Strategy
  • Computer Science Background Systems, technical architecture, and computational foundations informing product and infrastructure design

Select Awards / Recognition

  • Google for Startups Founder Fund
  • AWS for Startups Founder Fund
  • National Science Foundation Grant (2x recipient)
  • Roddenberry Foundation
  • Camelback Ventures Fellow
  • Black Ambition Prize Recognition

Selected Talks & Speaking

  • Keynote: Future of Leadership + AI ALPFA Tech Summit
  • Panelist: Ethical AI, Work, and the Future of Opportunity Horizons Conference / Jobs for the Future
  • Panelist: Building AI as a Social Impact Entrepreneur Camelback Ventures Guardian Summit
  • Panelist: AI Adoption in Core Institutions University of Phoenix

Background

Over the last decade, my work has spanned:

  • AI systems
  • Product strategy
  • Infrastructure design
  • Enterprise implementation
  • Responsible innovation
  • Social impact entrepreneurship

I've led 50+ enterprise system implementations, built NSF-funded research, partnered across startups and institutions, and increasingly focused my work on a singular question:

How does intelligence behave in systems?

That question is now the foundation of everything I build.