Building accurate AI without clean data

Let’s be real — clean semantic layers are a dream come true. And even when you get there, the context is constantly shifting: new data sources, evolving definitions, and changing business logic.

So how do you build AI systems that stay reliable through all of that?

In this quick lightning talk, we’ll show how PromptQL helps teams ship CompanyQL — a domain-specific planning language that encodes your unique semantics, tribal knowledge, and business logic into something LLMs can execute deterministically.

00:00 Intro
01:16 The Messy Data Reality
03:08 The Failed Promise Timeline
04:13 Why Semantic Layers Fail?
05:54 The Knowledge Graph Delusion
07:02 The Real Problem
08:36 Enter the Agentic Semantic layer
09:57 PromptQL Day 0 (Smart Analyst)
12:00 Demo Time
13:41 PromptQL Day X (Veteran Analyst)
14:43 Question 1: Analysis
16:20 Question 2: Analysis
16:36 Question 3: Analysis
16:53 Demo: How PromptQL Learns
19:39 Autograph: Technology that Powers the Learning
22:31 The Learning Advantage
22:55 Results That Matter - $100M impact, data still a mess
23:08 Testimonials
23:38 Wrap : )
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PromptQL is the AI platform that delivers human-level reliability for natural language-based analysis and automation on your data & systems.

Check out our features:
https://promptql.io
LinkedIn
linkedin.com/company/promptql-io
Forum
forum.promptql.io
Twitter
x.com/promptQL
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Видео Building accurate AI without clean data канала PromptQL