AI Code Intelligence.

The industry gives agents a search box. Prism gives them a navigation system.

Turn your entire codebase into a searchable, AI-ready knowledge base — for every AI coding agent and every developer on your team.

Try it Out

56%Avg. Token Reduction
48Languages Supported
<10sIndex Freshness

“Context files tend to reduce task success rates compared to providing no repository context, while also increasing inference cost by over 20%.”

ETH Zurich

arXiv:2602.11988, Feb 2026

The Bottleneck Isn't the Model. It's the Context.

On real enterprise codebases — 50K, 200K, 500K+ lines — both AI agents and human developers struggle with the same three failures:

Failures
AI Agents
Human Devs
Blind Exploration
Burn tokens reading irrelevant files. A 5K-token task costs 15K.
Spend weeks building a mental model from scratch, asking colleagues for context.
Missing Context
Hallucinate APIs that don't exist — the agent never found the right module.
Get blocked on the one person who knows that module. Bus factor = 1.
No Big Picture
Can't hold 200K lines in a context window. Navigate by guessing.
Can't see architecture across repos. Cross-team questions require interruptions.

We have built enterprise software for over a decade. We know this problem first-hand: outsourced teams rotate, vendors get replaced, internal restructurings dissolve entire departments. Each transition triggers weeks of handover — documentation, knowledge sessions, co-coding — without moving a single feature forward.

The knowledge is always locked in people's heads. When they leave, it leaves with them.

Both agents and developers need the same thing:

A map of the codebase that shows what matters, explains what it does, and stays current.

From Code to Intelligence. Five Stages.

The industry gives agents and developers a search box. Prism gives them a navigation system.

Every file goes through a five-stage pipeline. This powers both the MCP tools (for AI agents) and the Console (for developers). One intelligence layer, two channels.

Intelligent Chunking

Breaks code into functions, classes, methods using Tree-sitter AST. 48 languages.

Semantic Embedding

Converts each chunk into a 2,000-dimensional vector. Search by meaning, not keywords.

LLM DescriptionUNIQUE TO PRISM

Writes a plain-English explanation for every chunk. Separately embedded for intent-based search.

Architectural MappingUNIQUE TO PRISM

Builds an import graph, scores every module with PageRank. Reveals the structural spine.

Multi-Signal Storage

Stores everything in an isolated, searchable knowledge base per tenant.

What Makes Prism Different.

LLM-Enriched Code Descriptions (Stage 3)

For every code chunk, an AI model writes a 1–2 sentence plain-English description. That description gets its own embedding — enabling two semantic search channels: Semantic (code vectors) finds code that does similar things regardless of naming, and Semantic (description vectors) finds code whose AI-generated description matches the developer's intent.

PageRank Architectural Mapping

Prism builds an import-dependency graph across the entire codebase and scores every module by structural importance. Core files imported by dozens of others rank highest; leaf utilities rank lowest. Agents and developers see the structural spine first.

Three-Tier Live IndexingTier 1 · File Watch
< 10s
Every save updates the index instantly
Tier 2 · On-Commit
< 30s
Team index updated on every commit. Branches stay current.
Tier 2 · On-Push
1-5 min.
Full reconciliation. PageRank map rebuilt.

4-Way Hybrid Search A Superset of Grep and Glob.

Prism runs four search strategies in parallel and fuses the results using Reciprocal Rank Fusion. It finds everything grep and glob find — plus meaning-based matches they can't. Reciprocal Rank Fusion fuses results from all four methods. A code chunk found by multiple strategies ranks highest.

Semantic (code vectors)
Finds code that does similar things, regardless of naming. "rate limiting" → finds _throttle_request()
Semantic (descriptive vectors)
Finds code whose AI-generated description matches your query. "validate JWT" → finds _validate_rs256_sig()
BM25 keyword
Exact keyword matches in code text — like grep. "webhook_secret" → finds all references
Exact substring
Precise string matches — grep and glob equivalent. "def handle_ingest" → finds the exact function

MCP Navigation Tools

Prism exposes specialised navigation tools via MCP, available to any compatible AI coding client.

Two steps: add the Prism MCP server, add an agent instruction file. Done.

No plugins, no infrastructure, no vendor lock-in.

Claude CodeCursorWindsurfCodex

Console Wiki & AI Architect

For human developers: a web-based Console with a living Wiki auto-generated from code and always in sync, and an AI Architect that answers any question about your codebase with code-referenced responses. No IDE required.

Prism Console: Dashboard, Wiki, and AI Architect

The Numbers

55.9%Average Token Reduction

Benchmarked across 20 diverse coding tasks. Savings scale with codebase size.

Small25.5%
< 300 LOC
Medium41.5%
300-1,000 LOC
Large58.9%
1,000-2,000 LOC
Very Large66.9%
1,000-2,000 LOC

More Reliable Output

Precise context prevents API hallucination. Confidence scores guide deeper exploration.

Faster Task Completion

Right context on the first try. Agents reason about code instead of searching for it.

Architectural Awareness

PageRank mapping means agents produce code that fits the existing architecture.

How Prism Compares

Feature

Augmented Code

Greptile

MCP Navigation Tools
✓Specialised navigation tools
✓Context Engine via MCP
✕API only

PageRank Architecture
✓Import graph + ranking
✕No
✕No

Hybrid Search (4-way)
✓Semantic + BM25 + desc + exact
—Semantic search
—Semantic + code graph

LLM Code Descriptions
✓Every chunk, separately embedded
✕No
✕No

Web Console / Portal
✓Full dashboard + admin
✕IDE-only
—Web app (limited)

Living Wiki
✓Auto-generated, always in sync
✕No
✕No

AI Architect
✓Conversational, code-referenced
—Chat in IDE
—Web Q&A

Live Indexing (< 10s)
✓3 tiers, file-watch level
—Real-time in IDE
✕On-push only

European Data Sovereignty
✓EU hosted, self-hostable
✕US-based
—Self-hosted option

Pricing Model
✓Flat per-seat, no overages
✕Usage-based (unpredictable)
—Per-seat + per-review

✓ Full support— Partial✕ Missing

Pricing

Free

CHF0,00

✓ 1 developer
✓ 1 repo up to 100K lines
✓ On-push indexing
✓ All MCP tools
✓ Console Wiki (read-only)
✓ AI Architect (20 questions/day)

TeamMost popular

CHF35,00

/dev/month

✓ Unlimited developers (min. 3)
✓ Up to 10 repositories
✓ All 3 indexing tiers (file watch)
✓ AI reranker for search quality
✓ Full Console Wiki (edit + export)
✓ Unlimited AI Architect

Enterprise

CHF65,00

/dev/month

✓ Unlimited developers (min. 10)
✓ Unlimited repositories
✓ Priority indexing queue
✓ Wiki export
✓ Audit log
✓ SSO/SAML
✓ Dedicated Slack support (4h SLA)

- (Team Plan)

Augmented Code

Greptile

CHF 35 / dev
Flat per-seat (no overages)
CHF 55 / dev
Credit-based (unpredictable)
CHF 30 / dev
Per-seat + per-review