Our Research: The Science Behind Predictable Results
We don't rely on buzzwords; we rely on evidence. Our platform is built on a foundation of peer-reviewed research to de-risk your most critical decisions around hiring, performance, and security. Here is the proof.
Key Publications
Our foundational, peer-reviewed research and strategic guides that underpin our entire methodology.
Platforming the Nearshore IT Staff Augmentation Industry
This Amazon-published book is a strategic guide for executives on how to leverage nearshore teams to accelerate growth, innovate faster, and build a more resilient organization. It provides a practical framework for navigating the challenges and capitalizing on the opportunities of the modern global talent landscape.
AxiomCortex™: Scientific R&D Report — Bias-Mitigated AI Evaluation for Nearshore Software Engineering Teams
Our peer-reviewed paper detailing the proprietary Cognitive AI engine that powers TeamStation AI's talent evaluation, outlining its core scientific pillars and bias mitigation strategies.
Heuristically Trained Neural AI for End-to-End Nearshore IT Staff Augmentation
This paper introduces a novel framework for predicting hiring timelines and optimizing the recruitment process, demonstrating a significant reduction in Time-to-Hire.
A Scientific Framework for Measuring Human Capacity in Nearshore Software Engineering
A comprehensive overview of the TeamStation AI platform architecture, its core AI technologies, integrated services, and responsible AI principles.
Nearshore IT Talent Performance Metrics in the Age of AI
This paper proposes a novel, value-centric model for assessing software engineer performance, moving beyond outdated metrics to focus on quantifiable impact.
Listen to the Platform Vision
Hear directly from our founders and technical leaders about the science and strategy behind TeamStation AI.
The Nearshore IT Co-Pilot™
Listen on Spotify to learn about the platform vision from our leadership.
Listen Now on SpotifyIs your hiring process a high-risk gamble on resumes?
The Science of De-Risking Talent
This is the definitive public documentation of the proprietary Cognitive AI engine that powers our talent evaluation. It's the science behind how we provide evidence-based proof of a candidate's problem-solving ability, not just their credentials.
Read the ProofCan you defend your hiring decisions with data?
The Evidence Locker in Action
This is not a paper, but a real, tangible output of our research. See an anonymized evaluation report and the 'Evidence Locker' that turns hiring from a gut-feel guess into a defensible, data-driven science.
Read the ProofAre outdated metrics failing to capture true engineering value?
Measuring What Matters
In the AI-augmented era, 'lines of code' and 'tickets closed' are meaningless. This research proposes a novel, value-centric framework for measuring engineering performance based on outcomes, not outputs.
Read the ProofIs your onboarding process a black box?
Proof of Performance
See how we apply our framework in the real world. This example report shows how we establish a data-driven baseline for a new engineer's performance within the first 30 days, creating an immediate, actionable growth plan.
Read the ProofA CTO's Questions, Answered by Science
The strategic questions our research directly addresses.
How can I be sure a candidate who interviews well will actually perform?
I've been burned by charisma before.
This is the exact problem our Axiom Cortex™ was built to solve. Traditional interviews are flawed because they conflate communication style with technical ability. Our process measures 'Problem-Solving Agility' through structured, bias-aware evaluations. We provide an auditable Evidence Locker so you're judging the logic, not just the presentation. This is how we de-risk the hire.
How is your 'Cognitive AI' different from a keyword scanner?
Everyone claims to use AI in hiring.
Simple: we use Cognitive AI for psychometric analysis, not just resume parsing. While others use a generic LLM API call to find keywords, we use our proprietary, peer-reviewed models to score a candidate's latent cognitive traits. Our research outlines how we separate the signal (true ability) from the noise (jargon, fluency). It's the difference between finding someone who has 'used' a tool and someone who can 'think' with it.
How do I measure the real impact of my engineers?
My current performance reviews feel subjective.
Our research into a Performance Evaluation Framework directly tackles this. We're building a system that moves beyond 'tickets closed' to measure true value creation. It correlates engineering activity with business outcomes. It's about shifting the conversation from 'How busy are you?' to 'What impact did you have?'
Ready to Apply the Science?
Let's move from theory to practice. In a 15-minute call, we can show you how our research-backed platform can solve your specific challenges.
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