SignalPilot AIGet To Insight
100x Faster
From “why did this change?” to full analysis
in minutes, not days
Built by and for people who live in notebooks
Data scientists, ML & Analytics Engineers, Quants, Researchers, and Technical Founders
SignalPilot
"Why did MRR drop 8% this week?"
Answered in minutes. With sources. Ready to share.
Per investigation, every time
And it gets smarter each time
Core CapabilitiesBuilt for Data Teams that Ship
Context-aware AI that understands your environment, plans ahead, and delivers production-ready insights
Understand your data and code
Scan warehouses and databases to use real models, columns, and contracts in queries and joins
Read local repositories and helper files to call functions with correct arguments and return types
Plan & code accurately
Generate multi-step plans with explicit assumptions, tables, and filters before writing code
Create environment-aware Python and SQL that respects installed libraries, versions, and organizational rules
Leverage notebook state to continue from existing variables instead of redefining everything
Visualize & interpret
Create high-fidelity plots including complex layouts like facets, multi-axis charts, and small multiples
Generate concise interpretations that highlight trends, outliers, and key insights for decision-makers
ArchitectureConnectConnect, AskAsk, PlanPlan, LearnLearn
Full Org Context is All You Need
Enterprise ReadyEnterprise-Grade Data Security
Other AI tools require uploading sensitive data to third parties. SignalPilot runs where your data already lives.
Local & VPC Deployment
Deploy on-prem, in your VPC, or on your laptop
Zero data exfiltration—queries stay inside your perimeter
Works with existing security policies and compliance frameworks
Bring Your Own LLM
Local-first design for the agent and notebooks
Use Claude Opus 4.5, GPT-5, or fully air-gapped local models
Stateless inference—nothing logged, nothing retained
Granular Data Controls
Scope model access per-project or per-notebook
Complete audit trail of every query the model sees
Auto-redaction and sampling for PII and sensitive fields
Built for SOC 2, HIPAA, and enterprise security reviews
Agentic HarnessThree Pillars Converging
SignalPilot brings the deepest context orchestration and the best models together in an iterative agentic harness
10+ first-class database and warehouse connection sub-agents that understand your schema, relationships, and business logic.
SnowflakeSlackNotionClaude Opus 4.5 for deep reasoning paired with fast, high-throughput models for summarization and routing.
Claude Opus 4.5
ChatGPT 5.2RLM-like reasoning loops with custom skills and rules, using Jupyter Notebook as the agentic harness.
JupyterSignalPilot
Metric Intelligence Copilot
Who It's ForFaster investigations.
Verified answers.
No bottleneck.
For practitioners who want to move 10-100x faster — and leaders who need answers without waiting on the data team.
Verified answers without the 3-day wait
Stop waiting on the data team to investigate why metrics moved. Get notebook-backed answers you can trust — in minutes, not days. Show up to board meetings with the analysis already done.
Turn your team from ticket queue to strategic asset
Every ad-hoc request pulls your best analysts off high-leverage work. SignalPilot handles the investigation backlog — so your team can finally focus on models, pipelines, and projects that move the business.
10-100x faster metric investigations
What used to take hours of SQL, slicing, and hypothesis testing now takes minutes. SignalPilot runs the diagnostics — you review the findings and ship. More time for the ML work you actually want to do.
Move faster with verified analysis at your fingertips
Know why conversion dropped. See if that experiment moved the needle. Get the analysis you need to make decisions and ship — without being blocked by the data team's backlog.
We built SignalPilot because we were tired of debugging AI code that never understood our real data stack