Data Analytics Tool For Interpretable Dependencies
Make Smarter Decisions
with Interpretable AI
Unlock the "why" behind your data — in minutes, not months.
DATFID helps business leaders and analysts get explainable, revenue-driven forecasts from complex product data — instantly and without black-box models.
Built for Decision-Makers Who Need Clarity, Not Code
Whether you're a CEO, CDO, Head of BI, or Product Manager — you've probably asked:
CEO
"Why are revenues dropping?"
CDO
"What really drives sales across our product lines?"
Head of BI
"Can we trust this forecast?"
Product Manager
"How do pricing changes impact demand?"
DATFID helps you answer these questions with full transparency — Get the power of hedge fund analytics without hiring a Ph.D. team.
AI Promises a Lot — But Delivers Black Boxes
"AI tells you what, but not why. And why is what leaders need."
💡 Did you know? Explainable AI ≠ Interpretable AI. Explainable AI tries to explain black-box decisions after the fact, while Interpretable AI (like DATFID) builds transparency into the model from the start.
From Data to Decisions — Without the Black Box
Upload your product data (Excel or API)
Works with multiple products, regions, stores.
Run DATFID
No model training, no tuning — just results.
Get a clear, mathematical forecast
Example: Revenue = 4.3 × Price + 2.1 × Promo – 0.9 × Traffic
🔍 Proven Accuracy
Outperformed all published benchmarks in the M5 Forecasting Accuracy challenge, scoring 0.64, ranking in the top 5%— all achieved zero-shot, with full interpretability.
📊 Real-World Validation: Tested on Walmart's actual retail data — 3,049 products across 10 Stores in 3 US states over 1,941 days, including sales, prices, promotions, and events. This real retail forecasting challenge demonstrates DATFID's ability to handle complex, multi-dimensional business data with enterprise-scale accuracy.
Accuracy Score
Global Ranking
No Training Required
Works Where You Work
Python SDK and REST API
Integrates with Excel, BI tools, ERP
Supports multi-product, multi-store panel data
No data preprocessing needed
from datfid import Client
model = DATFIDModel(
file_path,
time_column="Date",
entity_column="ProductID",
features=["Price", "Promo", "Traffic"]
)
forecast = model.forecast()
print(model.summary())More Clarity. Less Guessing. Measurable Results.
Save 60% of analysis time
Reduce BI/DS backlog instantly
Full model transparency
Know why performance changes
+20% revenue from better accuracy
Real-world case: coffee pricing in retail
No DS team needed
Works via API + Excel
Fast time to value
Go from raw data to insights in 1 day
From Confusion to Control: A Coffee Case Study
A gas station chain wanted to optimize pricing across 100+ locations. DATFID's panel analysis found hidden demand patterns — resulting in
in revenue potential (at national scale)
faster than Neural Nets
interpretablity power (vs. 10–20% from AI/ML)
Trusted by Analysts, Professors and Founders
"This tool can make our world better."
Ron Fridman
Forbes 30 Under 30, CEO Mawi
"Excellent tool with novelty and trustworthiness."
Beatriz Hoffmann-Kuhnt
CEFoodCycle Project
"Great for data analysis and forecasting."
Nina Hubig
Asst. Professor, Linz University & MUSC, Charleston
