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Depth AI

Paid

Build a living knowledge graph of your codebase and deploy secure AI assistants everywhere.

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#AI#Developer Tools#Codebase#Knowledge Graph#Technical Question-Answering#System Design#Repo-aware#AI Assistants#Slack#GitHub Copilot#Jira#Enterprise Security
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About Depth AI

Depth AI builds a comprehensive knowledge graph of your codebase to power deep technical question‑answering, abstract system design reasoning, and repo‑aware chat. It combines code graph analysis with latent‑space understanding, then lets you deploy custom, permission‑aware AI assistants into developer workflows like Slack, GitHub Copilot, Jira, and an API—backed by enterprise‑grade security with self‑hosting, audit logs, and end‑to‑end encryption.

Key Features

Code graph understanding across repositories and components
Abstract reasoning on system design and architecture
Latent‑space interactions for semantic code understanding
Custom AI assistants scoped to specific files, folders, or services
Seamless integrations with Slack, GitHub Copilot, Jira, and API
Enterprise‑grade security with no training on your data
Self‑hosted deployment in your private VPC
Real‑time permissions with detailed audit logs
End‑to‑end encryption (AES‑256 at rest, TLS 1.2+ in transit)
Direct codebase chat for deep technical Q&A

Pros & Cons

Pros
  • Deep technical question answering beyond simple code search
  • Code graph construction enables abstract reasoning about system design
  • Latent space interactions capture semantic meaning and patterns
  • Custom assistants can be deployed to multiple surfaces (Slack, GitHub Copilot, Jira, Web App, API)
  • Enterprise-grade security with zero training on customer data
  • Self-hosting option for data sovereignty
  • Real-time permission enforcement and audit logs
  • API-first design for integration flexibility

Best For

Staff engineers: Ask architecture‑level questions and evaluate design tradeoffs using a live code graph.SRE/DevOps: Trace dependencies to accelerate incident response and root‑cause analysis.New hires: Onboard faster by chatting with the codebase and receiving guided explanations.Platform teams: Plan refactors or migrations by understanding service boundaries and call graphs.Security/compliance: Map data flows and verify permission‑aware access with auditability.Backend engineers: Locate relevant modules, contracts, and side effects to speed up debugging.QA/Testing: Perform test impact analysis and identify affected components from a change.Product/TPM: Get plain‑language explanations of how features work across services.Docs/DevRel: Generate and maintain architecture overviews and developer docs from the graph.Support engineers: Reproduce and triage customer issues by following dependency paths in code.

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