AI Data Platform for Data Engineers
Build Data Agents You Can Trust
Describe what you would like your agent to do – or choose a use case below.
Start free. Keep your existing stack. Use sample data or connect your own.
Install the Jedify MCP in Claude or ChatGPT skill to connect agents to your Contextual Data Layer:
npx @jedify/mcp install
Build Semantic Agents
Jedify’s Semantic Fusion™ Model translates your messy, multi-source data into a unified context layer – so AI agents can ask real questions and get accurate, grounded answers. No prompt engineering. No hallucinations. Just business logic, encoded once and used everywhere.
Why data teams choose Jedify
Schema-aware context
Jedify maps your semantic layer so agents understand what each metric means in your business – not just what the column says.
Multi-source fusion
Connect warehouse, CRM, and product data. Jedify joins it correctly with full business context across every source.
Built for operators
RevOps, product, and marketing teams define their logic once. Agents use it reliably – every query, every time.
No hallucinations
Every agent answer is grounded in real schema and business rules – not guessed from model weights or stale context.
Start with a use case
Pre-built agents for common analytics workflows. Click to load a prompt.
use case 01
Risk monitoring
Track key metrics in real time and get alerted the moment something breaches a threshold.
use case 02
Data quality
Automatically detect data quality issues and inconsistencies before they impact decisions.
use case 03
Operational forecasting
Use live signals to predict future trends and recommend proactive actions that protect the bottom line.
use case 04
Pricing intelligence
Compare our pricing against competitors by product line, highlight gaps, and estimate margin risk.
use case 05
Web data comparison
Compare competitor product pages, reviews, and category trends, then summarize the biggest shifts.
use case 06
Real-time advertising analysis
Combine spend, pipeline, CAC, ROAS, and revenue data in real time and tell me where to shift budget today.
use case 07
Churn detection
Score accounts by churn risk using product usage, support history, and engagement signals – and flag which ones need attention now.
From connected data to useful answers in minutes
Pre-built agents for common analytics workflows. Click to load a prompt.
Step 01
Connect your data warehouse or start with sample data
Step 02
Jedify builds your semantic layer - mapping tables, joins, and business rules into AI-ready context
Step 03
Agents answer in plain language - grounded, accurate, and ready to act on
Analyze big datasets with context, not AI guesswork
Jedify gives your AI agents a semantic foundation – so they answer accurately, explain their reasoning, and scale with your data.
