Every decision,cited.
CitedIn is a new AI data science platform that turns the data you already have into predictive models — churn, demand, risk, pricing — where every prediction traces back to the exact data that drove it. We're building in private beta.
Designed to run on your warehouse — Snowflake · BigQuery · Databricks · Postgres
Predictions cited
100%
traced to source
Model lift
vs. baseline heuristic
- churn-risk-v4live94.2%
- demand-forecastlive91.8%
- credit-defaultlive88.5%
- price-elasticitytraining86.1%
The problem
Most companies have the data. Almost none can act on it in time.
The backlog
Your dashboards describe the past.
Every team is drowning in BI dashboards that report what already happened. By the time a human reads the chart and reacts, the moment — the churn, the stockout, the fraud — is already gone.
The bottleneck
Data science can't ship fast enough.
A single production model takes months: pipelines, feature stores, review, MLOps. The average enterprise ships fewer than four models a year while hundreds of decisions still run on gut and spreadsheets.
The cost
The decisions run without a model.
Pricing set by committee. Inventory ordered on last year's numbers. Risk flagged after the loss. Each one is a model waiting to be built — and revenue quietly leaking while it isn't.
We're building CitedIn so any team can turn the tables they already have into decisions that act in real time — and show their work.
— Why we're building CitedIn
The platform
From raw table to live decision — without the two-quarter project.
CitedIn is designed to collapse the entire ML lifecycle into three steps your existing team can run end to end.
Connect
Point CitedIn at your warehouse. It profiles every table, infers the schema and relationships, and surfaces the columns worth predicting on — read-only, no pipelines to build.
- Snowflake · BigQuery · Databricks
- Auto feature discovery
- Read-only, in your VPC
Model
Pick an outcome — churn, demand, default, price. CitedIn trains, validates, and benchmarks candidate models against your baseline, then cites every driver behind a prediction.
- AutoML + human-readable specs
- Backtested against baselines
- Full feature attribution
Automate
Ship the model as a decision: a scored API, a warehouse write-back, or a triggered action in the tools your team already uses. Monitored for drift, retrained on a schedule.
- Decision API + webhooks
- Drift & performance alerts
- Scheduled retraining
Solutions
One platform. Every decision your data can make.
Churn prevention
Flag at-risk accounts before they leave
Demand forecasting
Predict what sells, where, and when
Fraud & risk
Score transactions the moment they land
Dynamic pricing
Set prices from live elasticity signals
Lead scoring
Rank pipeline by likelihood to close
Predictive maintenance
Catch failures before they happen
Built for
The whole team that turns data into decisions.
Heads of Data & Analytics
Clear the model backlog without hiring. Give your analysts a way to ship production decisions themselves, with governance and lineage you can defend in an audit.
Data Engineering & Platform
No new pipelines to maintain. CitedIn reads from the warehouse you already trust, runs inside your VPC, and writes decisions back where your systems can consume them.
Operations & Revenue leaders
Stop waiting on a queue. Turn the decisions you make on spreadsheets today — pricing, targeting, inventory — into models that run continuously and explain themselves.
Coming soon
Be first on CitedIn.
We're opening the private beta soon. Join the waitlist and we'll reach out when it's your turn — plus early notes on what we're building.
No spam · Just a heads-up when the beta opens at getcitedin.com