EvalAim is the assessment platform built for AI upskilling programs. Structured exercises, rubric-based LLM scoring, and live workshop tooling — so you walk away with evidence, not a completion percentage.
You invest in an AI program. People show up. They watch demos. They take notes. They leave feeling confident.
Three weeks later, your team still isn't using AI effectively — and you have no idea why.
The problem isn't effort. It's that almost every AI program stops at awareness. They teach people about AI, but never verify whether those people can actually produce useful output with it.
EvalAim is a workshop and assessment platform — structured exercises, immediate LLM-evaluated feedback, and reports that show exactly where each learner stands. Participants don't read slides; they write prompts, author skills, and work with real data. Every submission is scored by a fixed five-dimension rubric.
Each prompt, skill, or analysis is evaluated against the same public rubric — same scoring the trainee sees, no expert-reviewer bottleneck.
Dimension scores, concrete suggestions, and narrative feedback land instantly. Learners iterate inside the same session, not next week.
When the cohort closes, you walk away with a per-learner gap analysis, integrity digest, and CSV/PDF exports — not just an attendance sheet.
Most AI programs end with a completion percentage. EvalAim ends with dimension-level capability data, integrity evidence, and exportable proof of learning — the materials your stakeholders actually want.
A fixed five-dimension rubric — persona, task, context, format, constraints — applied identically to every submission. You see why someone scored what they scored, and so do they.
QR-code join, PIN access, projector-ready leaderboard. Everything an instructor needs to run a smooth in-room session — with or without a setup team.
Dimension scores, suggestions, and narrative — generated immediately. Learners revise in-session.
Heatmaps surface which learners struggle on which dimensions — so you target coaching, not retraining.
Paste detection, focus-loss, devtools alerts. Flagged for review. No auto-blocking, no false accusations.
CSV exports, styled PDF readiness reports, printable certificates — the artifacts that L&D and compliance teams actually attach to a record.
One rubric. Three exercise types. Same scoring vocabulary across the platform — so a learner's profile reads consistently from prompt-writing to skill-authoring to data analysis.
Participants get a realistic scenario and write a prompt to solve it. The LLM judge scores the submission across five fixed dimensions and returns specific, dimension-level feedback within seconds. Learners revise and resubmit in-session.
— The judge critiques the prompt. It does not execute it. The score is grounded in writing quality, not stochastic model output.
Participants author an AI agent skill — a structured definition that tells an AI how to handle a class of tasks. EvalAim runs two parallel calls — with-skill vs. baseline — and the score is the measured delta.
— The strongest defensibility moment in the platform: the score is grounded in measured improvement, not opinion.
Participants upload a CSV and ask questions in plain language. EvalAim plans the operation; the platform executes it safely and renders the result. Learners practice analytic phrasing — not pandas syntax.
— Numbers are computed, not generated. The LLM never invents a value.
Create a cohort, attach exercises, generate a QR code. Open or close activities live, reset PINs, remove participants — all from one dashboard.
Adjust labels and descriptions per organization so scoring language matches your internal AI competency framework, not a generic template.
Describe a topic; EvalAim drafts quiz tasks or skill challenges. Authors review, edit, and publish — content time drops materially.
Readiness summaries, weakness heatmaps, integrity digests, evidence packs — all per cohort and per organization, CSV or styled PDF.
No lengthy IT setup. No participant accounts. The whole loop fits inside a single workshop block, and every step produces a tangible artifact.
Name the cohort, attach the exercises, set the rubric. Generates a QR code in seconds.
Scan, enter a display name and PIN, see the activities. No email, no account creation.
Each submission scored against the rubric. Dimension feedback returned in seconds.
Open the projector view. Scores update as submissions land. Coach in the moment.
Readiness report, gap analysis, integrity digest — CSV or styled PDF, on demand.
For in-room training: trainees join by QR, the projector shows live scores, the instructor exports a CSV when it's done. SSE under the hood, with polling fallback when the venue WiFi is hostile.
— Color-coded by performance band. Top row pulses subtly. The leaderboard doesn't need explanation in the room.
An L&D team rolls out a four-week upskilling sprint. Each session is an EvalAim cohort. By week four, leadership has dimension-level readiness data for every participant.
An AI trainer facilitates a 40-person workshop. The leaderboard projects on the wall. Exercises run in rounds; coaching is in the moment, based on what the platform surfaces.
A consultancy delivers an AI readiness program. EvalAim runs structured assessments at engagement start and end. The client receives a defensible before/after report as a deliverable.
Every score is explained at the dimension level. Learners and instructors see exactly why a submission scored what it scored. No black box.
Rubric labels, model selection, rate limits, and judge behavior are all admin-tunable. EvalAim adapts to your competency framework.
Platform UI and rubric feedback ship in Turkish and English. Additional languages on request.
Paste detection, focus-loss tracking, devtools alerts — on by default, surfaced for instructor review, never auto-blocked.
Provider-agnostic LLM evaluation. OpenAI, Anthropic, Google Gemini, or self-hosted via Ollama. Your infra, your choice.
CSV and styled PDF export available at any time, per cohort or per organization. Your data does not stay locked inside.
EvalAim gives instructors the tools to run structured, assessable AI workshops — and gives L&D leaders the data to prove it worked. Book a demo and see what a rubric-scored prompt session looks like in practice.
— A 30-minute live session walks through cohort setup, the leaderboard view, and a sample readiness export.