Context Engineering

Your knowledge, structured for AI

Context engineering is how you teach AI about your company. Upload once, and your brand guidelines, policies, and expertise flow into every conversation.

Context Manager
Uploading Sources
📄

Brand Guidelines.pdf

2.4 MB

100%
📊

Pricing Matrix.xlsx

856 KB

75%
🔗

company.com/about

URL

45%

AI Extracting Knowledge

Identifying categories and key information...

Brand
Pricing
Product
Context Library
Synced
Brand12 items
Voice guidelines
Logo rules
Color palette
Pricing8 items
Tier structure
Discount rules
Product15 items
Feature specs
Roadmap items
Legal6 items
Terms
Compliance
Uploading...

01 / Process

From documents to AI-ready knowledge

Expert& transforms your existing documents into structured context that AI can understand and apply intelligently.

01

Ingest

Upload files, paste text, or scrape URLs. We accept PDFs, docs, spreadsheets, and more.

02

Structure

AI organizes your content into AI-friendly formats with semantic categorization and confidence scoring.

03

Inject

Context flows into AI conversations automatically based on tool needs and user roles.

02 / Sources

Bring knowledge from anywhere

Your expertise lives in many places. Expert& pulls it all together into one searchable, AI-ready knowledge base.

01
PDF documents
02
Word & Google Docs
03
Excel & Sheets
04
PowerPoint & Slides
05
Plain text files

Drop files here

or click to browse

📄

Brand Guidelines 2025.pdf

2.4 MB

12 contexts
📄

Sales Playbook.docx

856 KB

Extracting...
🧠

AI Extraction

POWERED_BY_CLAUDE

Brand Voice Guidelines

brand_voice_guidelines
Marketing

Our brand voice is confident yet approachable. We avoid jargon and speak directly to...

Pricing Structure 2025

pricing_structure_2025
Sales

Enterprise tier starts at $500/month with volume discounts available for...

Compliance Requirements

compliance_requirements
Legal

All customer data must be encrypted at rest. GDPR compliance requires...

✨

3 contexts extracted

2 high confidence, 1 needs review

03 / Extraction

AI finds the knowledge that matters

Our extraction engine doesn't just chunk documents—it understands them. Each piece of context is identified, categorized, and tagged for optimal retrieval.

01

Semantic Understanding

AI identifies distinct concepts, not arbitrary text chunks

02

Auto-Categorization

Marketing, Sales, Legal, Engineering—sorted automatically

03

Confidence Scoring

High confidence contexts go live; others flagged for review

04

Smart Tagging

Keywords and themes extracted for intelligent retrieval

04 / Schema

Enterprise-grade context

Every context item is structured for optimal AI retrieval, with metadata that enables intelligent selection and injection.

context_schema.ts
interface CompanyContext {
  id: string;
  context_key: string;        // "brand_voice_guidelines"
  context_data: {
    content: string;          // The actual knowledge
    summary?: string;         // AI-generated summary
    examples?: string[];      // Usage examples
  };
  metadata: {
    category: Category;       // marketing, sales, legal...
    tags: string[];          // For discovery
    priority: Priority;       // Injection order
    scope: Scope;            // universal, team, role

    // Access control
    departments?: string[];
    required_roles?: string[];
    sensitive?: boolean;

    // Lifecycle
    created_by: string;
    expires_at?: Date;
    confidence: number;      // AI extraction confidence
  };
}
01

Scoped Access

Universal contexts apply everywhere. Team contexts stay in team. Role-based for specialists.

02

Priority Ordering

High-priority contexts injected first. Never exceed token limits with smart truncation.

03

Expiration Dates

Time-sensitive content auto-expires. Quarterly pricing? Gone when Q2 starts.

05 / Injection

The right context, at the right time

Not all context is relevant to every conversation. Expert& intelligently selects what to inject based on tool needs, user roles, and content matching.

01

Tool declares needs

Each tool specifies which context categories, tags, or specific keys it needs.

context_hints: ['brand_voice', 'pricing']
02

User roles checked

Sensitive contexts only injected if user has required role.

required_roles: ['sales', 'manager']
03

Relevance matching

Tags and categories matched. Higher priority contexts selected first.

SELECT * WHERE tags @> tool.hints
04

Context injected

Selected contexts formatted and injected into the system prompt.

// XML or text format based on tool config

Ready to structure
your intelligence?

Join our design partner program and get hands-on help building your context library.