StrataInsights

Strata vs. Hyperspell: External vs. Internal Context for AI Agents

The Missing Pieces of the Agentic Stack: External Context Infrastructure vs. Internal Memory Systems

If you're building agentic workflows, you've likely hit the context wall. Bessemer's State of AI 2025 identified it clearly: "Memory and context are the new moats... yet much remains unresolved: memory, context, governance, agency."

Strata and Hyperspell are both solving the context problem—but for fundamentally different context types. Here's how they complement each other in the agentic stack.

The TL;DR

Strata builds external context infrastructure. It transforms any company URL into structured, queryable intelligence about markets, competitors, products, and positioning—ready for agent consumption.

Hyperspell builds internal context infrastructure. It connects to your Slack, Gmail, Notion, and Drive to build a knowledge graph from your company's own unstructured data.

Think of it this way: Hyperspell knows what your team discussed yesterday. Strata knows what your competitors are building today.

The Core Problem: AI Agents Need Both Internal and External Context

Modern AI agents are clueless without context. They can reason brilliantly about abstract problems but can't answer basic questions like:

Most teams building agents start by solving internal context with RAG pipelines. They quickly realize that external context—market intelligence, competitive positioning, product analysis—is equally critical but lives in a completely different domain.

Two Different Context Layers

Strata: External Context Infrastructure

What it does: Crawls public company data and generates structured intelligence shells containing 50+ strategic signals about any company—product architecture, ICP, pricing, competitive positioning, market category, leadership signals, whitespace opportunities.

Data source: Public web (company websites, documentation, pricing pages, job postings, public content)

Output format:

Generated in: <2 minutes per company

Use cases for agents:

The key insight: External context about markets and competitors doesn't live in your Slack or Drive. It requires active web crawling, synthesis, and structuring of public company data.

Hyperspell: Internal Context Infrastructure

What it does: Connects via OAuth to your company's tools (Slack, Gmail, Notion, Drive) and builds a queryable knowledge graph from conversations, documents, and collaboration data.

Data source: Your company's private, internal data sources

Output format:

Integration time: Minutes (via pre-built auth components)

Use cases for agents:

The key insight: Your team's decisions, discussions, and documentation are scattered across tools. Agents need unified access without forcing you to rebuild connector infrastructure.

The Architecture Difference: Public Crawling vs. Private Integration

Strata's Technical Approach

  1. Input: Company URL
  2. Process: Crawl public pages, extract signals, normalize into schema, generate context shell + artifacts
  3. Caching: Pre-crawled cache for common companies accelerates generation
  4. Portability: Context shells are downloadable, shareable, and (soon) API-accessible
  5. No auth required: Operates entirely on public data

The output is a reusable "context shell" that can be queried, integrated into CRMs, fed to agents, or exported as human-readable reports.

Hyperspell's Technical Approach

  1. Integration: OAuth connections to Slack, Gmail, Drive, Notion, etc.
  2. Process: Continuous ingestion, embedding, knowledge graph construction
  3. Storage: Multi-tenant platform with user-scoped access control
  4. Retrieval: End-to-end RAG pipeline via API
  5. Privacy: SOC2 and GDPR compliant, enterprise-grade security

The output is API access to your company's collective memory, queryable by agents with proper authentication.

Who Uses Each (Hint: Often the Same Team)

Both products target technical teams building AI agents and workflows, but for different context needs:

Teams Using Strata

Example: A sales engineering team building an AI SDR that automatically researches prospects, identifies competitive positioning, and generates personalized outreach. The agent uses Strata to understand each prospect's product, market, and competitive landscape.

Teams Using Hyperspell

Example: A product engineering team building an AI PM assistant that helps with sprint planning, remembers past decisions, and surfaces relevant discussions from Slack and Drive.

Teams Using Both

Complementary Infrastructure for Agentic Rollouts

The most sophisticated agentic implementations use both:

Example 1: Sales Intelligence Agent

Example 2: Product Strategy Agent

Example 3: Partnership Evaluation Agent

Positioning in the Agentic Stack

Both are context infrastructure but at different layers:

Strata = External Context Layer

Hyperspell = Internal Memory Layer

Together they solve the "context gap" that limits most agentic deployments.

Pricing Models Reflect Different Integration Patterns

Strata:

Pricing reflects value per external company analyzed—each context shell enriches your agents' understanding of a market player.

Hyperspell:

Pricing reflects typical infrastructure costs—you're running continuous ingestion and retrieval on your internal data.

Integration Patterns

Strata Integration (Current + Roadmap)

Now (Manual portability):

V2-V3 (API-first):

POST /generate-shell { "url": "company.com" }
GET /shell/:id
→ Returns structured JSON for agent consumption

Future (Agentic layer):

Hyperspell Integration (Current)

// Connect user accounts
const token = await hyperspell.generateUserToken(userId);

// Query internal context
const context = await hyperspell.query({
  query: "What did we decide about API versioning?",
  userId: userId
});

// Agent consumes internal context
agent.addContext(context.results);

When to Choose Each (or Both)

Use Strata if your agents need to:

Use Hyperspell if your agents need to:

Use both if your agents need to:

The Bottom Line

Don't think of these as competing products. They're complementary infrastructure for different context domains.

Strata gives your agents eyes on the external world—markets, competitors, products, opportunities.

Hyperspell gives your agents memory of your internal world—decisions, discussions, documentation, history.

Most sophisticated agentic rollouts need both. The question isn't "which one?" but "which context layer are we building for first?"

External context (Strata) makes sense when your agents interact with markets, prospects, competitors, or partnerships.

Internal context (Hyperspell) makes sense when your agents support team productivity, knowledge access, or institutional memory.

Build for the context your agents actually need to be useful.

Building agentic workflows? Visit getstrata.ai for external context infrastructure or hyperspell.com for internal memory infrastructure.