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Don't stop at answers.

Turn your data into AI-powered operations — trusted decisions, real workflows built to scale.

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01 · Data Discovery · For IT teams and data owners

The agent maps your warehouse before you write a query.

Run discovery once. The agent scans your entire warehouse, infers relationships, and writes a structured schema report — used as context for every analysis that follows.

Any scale

Billions of rows, any warehouse, no sampling. Discovery runs on your full dataset.

Fully secure

Deployed in your environment. Data never leaves your VPC. SOC 2 compliant.

Any source

BigQuery, Snowflake, Redshift, S3, and more. Connect once, discover everything.

How discovery works
Run data discovery

acme-analytics·BigQuery

The agent connects to your warehouse, analyses schemas, detects table relationships, and writes a structured report — once. Used as context for every subsequent analysis.

Focus on the analytics dataset. Flag any churn-related columns.

Estimated time: 2–4 minutes

02 · Notebooks · For data scientists, researchers, and analysts

Build any analysis. Agent-assisted, always reproducible.

Notebooks bring data, code, and outputs together in one place. Run as many analyses as you need — Zerve scales compute automatically so every notebook runs in parallel, with every version auditable and ready to deploy or share.

Discovery complete. I'll build a Customer Analysis notebook — load data, segment by tier, calculate churn rate, and chart MRR trend.
Yes, and also kick off Churn Model and Revenue Attribution at the same time.
All three are running in parallel. Zerve scales compute automatically — no waiting.
Churn Model
running
train_xgboost
evaluate_holdout
export_model
Revenue Attribution
running
join_stripe_orders
calculate_ltv
segment_cohorts
Customer Analysis
Deploy
Report
load_customers0.8s
segment_by_tier1.2s
calculate_churn_rate3.4s
plot_mrr_trend
export_results
Running in parallel · 2 of 5 complete
Serverless · v3.1.0

03 · Deployments · For data scientists and ML engineers

Deploy any app or API. In your own environment.

Turn any notebook into a production app or API in minutes. Use any framework. Load notebook outputs with a single import. No rebuilding pipelines — and no separate platform.

Churn model notebook is ready. Want to deploy it as a Streamlit app?
Yes — on our AWS cluster. And add a FastAPI endpoint for the model too.
Both deployed. churn-app.zerve.app is live. /predict endpoint is ready. Logs streaming.
load_customers
calculate_churn_rate
train_xgboost
DS
ML
PM
Shared with teamLive
LogsHot reloadLive previewYour infrastructure

04 · Reports · For business stakeholders and leadership

One or more analyses. One polished report. In seconds.

The agent reads your notebooks, extracts the key results, and writes a structured report tailored for your audience — with verifiable, source-linked findings you can iterate on with AI.

How does team size affect retention?

Q3 Customer Performance

Acme Corp · v4 · Generated by agent · Oct 1, 2024

MRR Month-over-Month

AprMayJunJulAugSep
$0M+18%MRR
0%−0.3ppChurn
0+847Active customers

Q3 saw record retention, driven by the loyalty campaign launched mid-July. Collaborative accounts retained at 2.4× the rate of solo users, and mid-market expansion added 847 net new customers — the strongest quarter since founding.

From Ask AI

The July loyalty campaign drove 847 returning users and lifted MRR 18% in a 30-day window. Churn dropped to 2.1%, the lowest since Q1 2023. Collaborative teams onboarded 47% faster and engaged with 3.1× more notebook outputs.

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Sarah ChenCFO
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James RiveraHead of Growth
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Aisha MoyoData Lead
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05 · Collaboration

Every stakeholder. Deeper findings.

Share any report with your team. Each person chats with the agent about what matters to them — getting tailored answers from the same source of truth.

SC

Sarah Chen

CFO

Asking agent about Q3
What drove the Q3 revenue spike?
Waiting…
JR

James Rivera

Head of Growth

Asking agent about Q3
Which segment is churning fastest?
Waiting…
AM

Aisha Moyo

Data Lead

Asking agent about Q3
Is the churn model still valid?
Waiting…

No more ad-hoc requests. The agent handles every question, from every stakeholder, in real time.

What would you like to build?
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Platform — AI-Powered Data Operations | Zerve AI