
Sage AI
The AI-Powered Notebook
From raw data to insights—clean, transform, analyze, and build models at the speed of thought.
Get Sage Today
I spend more time getting data clean and wired up than testing ideas.
My notebook breaks every time the schema changes.
LLM copilots hallucinate code that doesn’t run.
Your Challenges, Solved with Sage

Sage Fixes the Notebook Grind.

Understands your dataframes, schemas, and code context.

Writes runnable Python (and SQL) you can inspect before execution.

Catches silent data errors early.

Private & local-first so sensitive data never leaves your stack unless you allow it.
Built by Leading AI x Data Experts

Goldman Sachs

Capabilities
What You Can Do in Sage
Clean & Transform Data in Minutes
Ask in plain English; Sage inspects columns, types, nulls, and range issues, then proposes and applies fixes (with code you can review).
Explore & Visualize Instantly
Plot trends, rollups, anomalies, correlations, or custom metrics from a prompt. Interactive tweaks: “log scale,” “filter 2022+,” “group by sector.”
🧠
Model Faster
Prototype ML / stats model libraries and compare performance across splits with auto-generated evaluation cells.
🔍
Context-Aware Code Generation
Sage reads the notebook state, variables, imported libs, and dataframes before writing code—so suggestions fit your environment.
📒
Multi-Notebook & Data Registry
Work on multiples notebooks at the same time. Reference dataframes across notebooks; keep canonical dataset context so Sage stops guessing column intent.
♻️
Automatic Course Correction
If code errors, schema changes, or better planning appears, Sage diagnoses and recommends fixes. Accept, edit, or re-run.



Privacy & Security

Privacy-First Architecture

Run Sage locally or in your VPC.

No data leaves your environment by default.

0 retention from Anthropic (or other cloud LLM) when using your own keys in stateless mode.

Enterprise Isolation

Bring your own LLM endpoints (Anthropic, OpenAI, local open-weights, on-prem HF).

Full telemetry control: off, anonymized, or granular.

Network-restricted / air-gapped deployment options.

Data Boundary Controls

Run Sage locally or in your VPC.

Per-notebook allow/deny which dataframes can be read by the model.

Redaction + sampling modes for sensitive columns.

Audit log of all model-visible data.

Sage AI
Sage: Your AI Assistant for Seamless Data Analysis
Sage's agent mode can complete tasks end to end. It does this quickly, while keeping programmers in the loop. Try it out by clicking AI Chat in the Sidebar.

Capabilities
Why Sage Beats Other AI Tools
Sage
Data-aware: inspects DF shapes, dtypes, NaNs
Notebook-native edits w/ diff + review
Error + schema change recovery
Private / VPC deploy
Built for quant & DS workflows
VS Code / Cursor
Limited inline context
May insert code fragments only
Blind to downstream breakage
Cloud-tethered
General coding
LLMs (Claude / ChatGPT)
Has no real data context
Dumps pseudo-code
Hallucinates results
Cloud-tethered
General chat
Prevents silent join mismatches & type coercion bugs.
Tracks notebook state across cells.
Runs where regulated data lives.
How It Works

Connect or Load Data
CSVs, Parquet, db connection, or API pulls.

Ask What You Need
“Profile missing data,” “merge trades w/ prices,” “fit LSTM vs ARIMA.”

Review & Run
Sage proposes code blocks; you approve, edit, or auto-run. Results feed back into the conversation.
Built for Teams That Live in Data

Who Uses Sage Today:

Quant research (equities, options, crypto).

Data science inside fintech & healthcare analytics.

RevOps / GTM analytics teams wrangling giant CSV exports.

AI research groups teaching from messy student notebooks.
Usage Patterns We See:

Daily data hygiene workflows.

Rapid model bake-offs in R&D sprints.

Debugging legacy notebooks without tribal knowledge.

Teaching: “Show me how to do X in Pandas.”


FAQs
Frequently Asked Questions
How does Sage compare to Jupyter?
Can I use my existing Jupyter notebooks?
Which models does Sage support
Is my data safe?
Does Sage visualize data?
Loved by World-Class Quants & Data Teams
Sage caught a join bug that would’ve cost us a week.

Quant PM
Multi-Strat Fund
Faster than pairing w/ a senior engineer for exploratory work.

Data Lead
Fintech Unicorn
Finally an AI tool I can run inside our data boundary.

Head of Data Platform
Healthcare
Sage
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CAREERS
fahim@sagebook.ai
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