Use Cases

Built for real-world AI workflows

Any workflow where an AI agent needs accurate, up-to-date data instead of hallucinated guesses. Here's how teams use Neuledge in practice.

@neuledge/context

AI Coding Assistants

AI coding assistants hallucinate APIs that don't exist, suggest deprecated patterns, and confuse library versions. The root cause: they rely on stale training data.

Context indexes the exact docs for the libraries in your project — the right version, the right API — and serves them to your assistant via MCP. Sub-10ms queries, fully offline, zero cloud dependency.

✓ Version-specific docs — no more outdated patterns
✓ Works offline — no rate limits mid-session
✓ Private — your queries never leave your machine

Index Next.js 15 docs locally:

$ npx @neuledge/context add https://github.com/vercel/next.js
$ npx @neuledge/context mcp

Your assistant now has accurate docs:

"What's the correct way to define
 metadata in a Next.js 15 layout?"

→ Answers with real API, not hallucinated one

@neuledge/graph

Customer-Facing AI Agents

Support bots that cite wrong prices. Sales agents that invent features. Chatbots that give outdated availability. When customer-facing agents hallucinate, you lose trust and revenue.

Graph gives agents structured access to live operational data — prices, inventory, order statuses, feature flags — through a single lookup() tool. Pre-cached, structured JSON, under 100ms.

✓ Live data — always current prices and availability
✓ Structured JSON — reliable for LLM reasoning
✓ Pre-cached — fast responses even under load

Connect to your product data:

const graph = new NeuledgeGraph({
  sources: {
    products: { url: "https://api.internal/products" },
    orders:   { url: "https://api.internal/orders" },
  },
});

Agent queries live data:

const price = await graph.lookup(
  "current price for Enterprise plan"
);
// { plan: "Enterprise", price: 299, currency: "USD" }

@neuledge/context

Internal Knowledge Bases

Company wikis, runbooks, design systems, internal API docs — your team has valuable knowledge scattered across repos and wikis that AI assistants can't access.

Context indexes private repos and Markdown documentation into portable SQLite files. Your team's AI assistant gets instant access to company knowledge — and none of it leaves your machine.

✓ Index private repos — runbooks, design systems, internal APIs
✓ Fully local — proprietary docs never leave your infrastructure
✓ Free for any team size — no per-seat licensing

Index your company's private docs:

$ context add ./internal-api-docs
$ context add git@github.com:acme/design-system.git
$ context add git@github.com:acme/runbooks.git

Team members get grounded answers:

"How do I set up the staging
 environment for the payments service?"

→ Answers from your actual runbook,
  not a generic guess

Context + Graph

CI/CD & Automation

Automated pipelines — code review bots, doc validation, migration scripts — need accurate data references just like interactive agents.

Both Context and Graph work headlessly in CI environments. Index docs at build time, query live data in deployment scripts, validate references before merging.

✓ Headless operation — no UI required
✓ Deterministic — same index, same results, every build
✓ No external dependencies — works in air-gapped environments

Index docs in CI pipeline:

# .github/workflows/docs.yml
steps:
  - run: npx @neuledge/context add .
  - run: npx @neuledge/context mcp
    # AI review agent uses indexed docs

Validate data in deployment:

const config = await graph.lookup(
  "feature flags for v2.3 release"
);
// Validate before deploying

Ready to ground your AI?

No sign-up, no API keys, no cloud dependency. Get started in one command.

Get Started View Integrations