Atlaz – Decoding Decision-Making with tacit knowledge and verifiability

Name: Atlaz – Decoding Decision-Making with tacit knowledge and verifiability
Availability: InStock
Author: RasmusBjersing

by RasmusBjersing·Mar 3, 2026·3 points·0 comments

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AI Analysis

●●SolidBig BrainSolve My Problem

Verifiable decision memos, not just AI answers—but adoption depends on enterprise sales, not product uniqueness.

Strengths

•Verifiability angle is genuinely clever: forcing traceable logic before recommendation reduces AI hallucination risk
•Interview-first UX captures tacit knowledge before jumping to answers, better than most AI tools
•Built-in integrations (Slack, Notion, spreadsheets) show enterprise thinking

Weaknesses

•Decision-support tools are crowded (McKinsey, BCG, internal templates); no clear evidence this outperforms human + spreadsheet
•Free tier unclear; pricing tiers ($20–$200) don't signal who this is for or what ROI looks like

Post Description

Hi HN, I'm Rasmus, Founder of Atlaz https://www.atlaz.ai.

Atlaz helps you make decisions by (1) interviewing you to capture tacit knowledge (context in your head) and constraints, then (2) generating a decision memo where key claims are backed by traceable analysis.

How it works: - You describe the decision (e.g., pricing change, hiring plan, vendor selection). - Atlaz asks follow-up questions to capture assumptions, constraints, and goals. - It produces a report you can share and collaborate on with teammates. For important claims, you can inspect supporting sources and the underlying analysis (scope/code/data).

What's different: Most AI tools jump straight to an answer that can be hard to justify. Atlaz extracts goals/constraints/assumptions first, and then gives you recommendations that you can easily review, scrutinize and share.

Video demo: https://youtu.be/EejvT6-Utc4

Pricing: free to try, paid plans $20, $100 and $200/month, or team pricing.