Hi, I'm Terezia.

Every company I've joined had no analyst relations program. I built each one from scratch, and the grids on this page are what came out of it.

I have a bias for action. When the tool, process or playbook I need doesn't exist, I build it. That's how my program ended up running on AI systems I designed myself.

The grids show what my programs delivered. What I've built and everything I've shared with the AR community show how much this craft means to me. AI is changing how analyst relations is done, and I intend to be the person defining what that looks like.

With AI rewriting the job, how long someone has done it says less every year. What counts is who can reinvent it. That's what I do.

Email terezia.stancik@gmail.com
linkedin.com/in/terezia-stancik
01

Analyst evaluations

Click any grid to see it full size
02

What I've built

Every AI workflow I run starts from a context layer I built.

How I build for analyst relations

I treat my context layer as an internal product.

The twin is one governed layer every AR workflow draws on, not a prompt per task.

Ontology over a semantic layer.

One is built to measure. The other gives a model meaning, so it can reason about my domain.

Capture the why, not just the what.

A context graph keeps the reasoning, exceptions and precedent behind each decision.

Analyst digital twin

The problem
AI drafts for analyst questionnaires read well but didn't know who would read them, or how each answer connected to the other 199.
What I built
My own enterprise context layer: an ontology and knowledge graph linking each analyst's research, calls and briefing history with our capabilities, proof points and roadmap.
80%of the AI-proposed wording kept in the final submission after expert review. Featured in Forrester research on AI in AR.
How it works ↗ The 80% check ↗

Novatera

The problem
Analyst evaluation RFIs: 200+ questions, several subject-matter experts and a two-week window, run out of spreadsheets.
What I built
An app for completing analyst evaluation RFIs. Each question comes with the analyst's scoring scale, last year's answer and sources, then moves through research, AI draft, validation and review. It started as my own internal tool and grew into Novatera, built with product and AI partners.
<5 daysto complete a major evaluation response, down from weeks. Demoed live at the Forrester AR Council in 2025.
The first version ↗ Forrester demo ↗ Launch ↗

Capability Gap Map

The problem
Analyst evaluations are the most expensive product feedback a company gets, and most of it ends up in a recap slide.
What I built
An interactive map combining evaluation scores, analyst feedback, competitive intel, enterprise RFPs and review data, tied to company priorities and filtered by persona.
Read the post ↗

My own AR CRM

The problem
Dedicated AR software was out of budget early in my career.
What I built
A tracker for every analyst interaction: a calendar, an interaction log with follow-ups, a cold map of who I haven't spoken to lately, an evaluation runway and a commitments list. No-code first, now fully custom-coded with a coding agent. Screens show sample data.
Read the post ↗
03

Speaking & media