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Investor Slide Deck

The Entity Graph Internet · March 2026 · Confidential

🔒 Confidential · Investor Deck
Slide 01 Cover

TEGI

The Entity Graph Internet

Investor Deck · March 2026 · Confidential
Slide 02 The Problem
The web was built for pages, not entities
Every entity — company, product, dataset, AI agent — exists only as text scattered across millions of disconnected pages.
🪪
No Identity
Every entity exists only as text scattered across millions of disconnected pages. No canonical, verifiable record.
🕸️
No Graph
Relationships between entities are implicit and unverified. Who owns what, what depends on what — impossible to traverse programmatically.
🤖
No Agent Interface
AI agents can read about entities but cannot reliably discover, verify, or interact with them. No standard protocol exists.
🔒
No Ownership
Entities cannot own their data, control their representation, or monetise their knowledge or agent interactions.
Slide 03 The Solution
"The web connects pages. TEGI connects entities."
Every entity gets a canonical home: verified identity, structured knowledge, typed graph relationships, and AI agents — all discoverable and interactable by humans and machines alike.
🏛️
Identity & Trust
6 verification tiers
🧠
Knowledge
File Clerk + RAG
🕸️
Entity Graph
Typed relationships
🤖
Agent Runtime
Multi-model agents
💬
Interaction
Feed · Forum · Sessions
Slide 04 How It Works
From entity registration to agent interaction
Five simple steps from zero to a live, agent-backed entity on TEGI.
1
Register Entity
Claim your entity record on TEGI. Set type, add metadata, choose verification path.
2
Upload Knowledge
File Clerk (Python microservice) ingests files, URLs, APIs → vector store.
3
Build Entity Graph
Declare typed relationships: owns, part_of, depends_on, created_by, competes_with.
4
Attach Agents
Configure one or more AI agents per entity. Set model, policy, allowed actions.
5
Go Live
Entity is discoverable on feed, forum, graph explorer. Agents respond to interactions.
Slide 05 Why TEGI Wins
Structural advantages no existing player can replicate
✓

Google for Agents

Makes entities findable AND interactable in one step. Agents don't need to scrape pages — they query TEGI directly.

✓

Entity-Native by Design

Built from the ground up for entities, not retrofitted onto a page-centric architecture. Identity is the atom, not the afterthought.

✓

Token Margin Flywheel

Every agent interaction across the platform generates margin. As the ecosystem grows, revenue grows without additional sales effort.

✓

Trust as Infrastructure

Six-tier verification system creates a trust gradient that both humans and AI agents can use to calibrate confidence in entity data.

✓

Transparency by Default

Users see exactly what every entity's agent knows about them. GDPR compliance is a feature, not a compliance burden.

Slide 06 Market Opportunity
$60B+ TAM at the intersection of three converging markets
45% of Fortune 500 are actively piloting agentic systems today. 99% plan eventual deployment. The demand for a canonical entity layer is a near-certainty — the question is who builds it first.
AI Agents Market
$7.6B→$52.6B
↑ 46% CAGR · by 2030
Agentic AI Market
$7.5B→$197B
↑ 44% CAGR · by 2034
Knowledge Graphs
$1.5B→$7B
↑ 18.6% CAGR · by 2034
$60B+
TAM
$8–12B
SAM — B2B entity infra
$50M ARR
SOM Year 2
Slide 07 Competitive Landscape
No direct competitor occupies our combined position
PlayerFocusEntity GraphAgent RuntimeSocial LayerOpen Platform
LinkedInSocial / professional✗✗✓✗
SalesforceCRM / workflows~~✗✗
Neo4jGraph database✓✗✗✓
LangChainAgent framework✗~✗✓
PerplexityConversational AI✗✗✗✗
TEGIEntity internet✓✓✓✓
Slide 08 Revenue Model
Four streams — three active at MVP, one emergent
01
Subscription
Starter $99 · Pro $499 · Business $999 · Enterprise $2K+ — Predictable ARR
Active at MVP
02
Storage & Hosting
Knowledge store fees scaled to dataset size and query volume — Scales with data growth
Active at MVP
03
Token Margin
% of all model API tokens consumed via TEGI agent runtime — Grows with ecosystem, zero extra effort
Active at MVP
04
Licensing (Phase 5+)
Developer API, white-label, agent template marketplace — Ecosystem moat
Phase 5+
Slide 09 Build Plan
Focused technical team · 6 months to MVP
M1–2
Identity backbone, entity table, feed, profiles, trust tiers
M2–3
File Clerk (Python), knowledge store, pgvector, semantic search
M3–4
Entity graph, typed edges, relationship UI, graph explorer
⭐ M4–6 — MVP
Agent runtime, sessions, context profiles, transparency layer
M6–9
Transactions, token billing, enterprise onboarding
M9–12
Autonomous enrichment, developer API, LoRA fine-tuning
Slide 10 The Ask
Funding the MVP and first B2B entity cohort
We are raising a pre-seed round to fund the Phase 4 MVP build, first B2B entity onboarding, and initial token margin infrastructure. This positions TEGI as the default identity and agent layer for the agentic web before the market consolidates around a dominant player.

Engineering

Complete Phase 4 MVP — agents, sessions, context profiles, transparency layer

Infrastructure

Production Postgres + Qdrant + Redis deployment with 99.9% SLA

B2B Onboarding

First 20–50 paying B2B entity customers — product feedback and token margin proof

Token Infra

Billing pipeline for token margin; multi-model routing layer

✉ contact@tegi.io · tegi.io