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About RecordorAI

AI that remembers.
Every client. Every conversation. Yours.

Every AI company has great models. Almost none have solved memory. RecordorAI is the persistent memory layer that makes AI agents actually useful across days, sessions, and users.

AI agents hit a memory wall.
Not a model wall.

Context windows are expensive and ephemeral

Million-token context windows exist โ€” but they're wiped at the end of each session. Paying for 1M tokens of context on every API call is cost-prohibitive for ongoing agentic workflows.

Memory doesn't survive across sessions

OpenAI and Anthropic are built for single conversations. An agent that needs to remember what a user decided three weeks ago, across a dozen sessions, is not a supported use case.

Inference cost compounds with history

Every extra turn of conversation adds to the context window. At 10K MAU, naive API-based approaches run $75โ€“180K/month in closed-provider fees โ€” before you're even profitable.

Data stays on third-party infrastructure

Every memory API call to a closed provider means your users' conversation history leaves your infrastructure. Enterprise customers won't accept that. Regulated industries can't.

The bottleneck isn't models. It's memory that persists.

Tiered memory architecture.
Built for agents that work.

RecordorAI sits between your AI agents and their context โ€” storing, compressing, and retrieving memory automatically. Your agents always have what they need.

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Tier 1 โ€” Hot

GPU KV Cache

5โ€“10K tokens of active context in GPU VRAM. Instant recall within a session. Zero latency. Costs $0.003 per 1K tokens on RecordorAI hardware โ€” 800x cheaper than GPT-5.4 for equivalent context density.

$0.003 / 1K tokens
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Tier 2 โ€” Warm

Semantic Vector Store

Full conversation history in pgvector + Supabase. Infinite retention, queried on demand. No per-token cost scaling with history length. Effectively free memory past the first retrieval.

Unlimited history
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Tier 3 โ€” Cold

Entity Compression

Each entity (user, project, decision) summarized into ~500 tokens. Extractive compression โ€” not generative. No hallucination risk. Costs almost nothing to store and retrieve.

~500 tokens / entity
Proven architecture:KV caching in vLLM and SGLang. Vector retrieval in every major search engine. Entity summarization is extractive compression โ€” no hallucination risk.

Simple revenue. Real margin.

$15/mo
Average revenue per user
Developer and Pro tiers
$4.23
Cost per user / month
OpEx only (infra + Supabase)
0%
Gross margin
After hardware depreciation
0
MAU to break even
$30K/mo revenue
Starter$15/mo โ€” 50K tokens/day
Pro$75/mo โ€” 500K tokens/dayPremium$175/mo โ€” 2M tokens/day
EnterpriseCustom โ€” Unlimited

One memory platform.
Multiple businesses.

RecordorAI's infrastructure hosts both its core inference business and a pipeline of vertical SaaS companies โ€” built using A.L.I.C.E. and sold to larger players in each space.

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Infrastructure

RecordorAI memory layer serves 10K+ users via API and chat UI

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Recurring Revenue

$150K/mo MRR at 10K users. Infrastructure contract never sold.

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A.L.I.C.E.-built Companies

Vertical SaaS products (CRM, AI assistants) built on RecordorAI memory

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Company Exits

Each company sells to a larger player. RecordorAI retains infra contract.

$3.5โ€“6.5M
1 company built, 10K users
$17.5โ€“32.5M
5 companies built, 50K users
$35โ€“65M
10+ companies built, 100K users

No royalties. Own your infra.

RecordorAI
OpenAI
Anthropic
Token royalties
$0 โ€” Apache 2.0
$2.50โ€“$15/M
$5โ€“$25/M
Context window
200K + tiered
200K
200K
Memory persistence
Cross-session
Token-limited
Token-limited
Own inference infra
Yes
No
No
Data stays on your infra
Yes
No
No
At 10K MAU, OpenAI/Anthropic API fees run ~$75โ€“180K/mo. RecordorAI infra: ~$14K/mo. That's a 5โ€“10x cost advantage โ€” permanent, not temporary.

The window opens H2 2026.

01

NVIDIA Vera Rubin (H2 2026)

10x inference throughput per watt. 1/10th cost per token vs Blackwell. Early infrastructure adopters gain a structural cost advantage that compounds.

02

Apple M5 Mac Studio (H2 2026)

Workstation-tier inference becomes real. RecordorAI's hybrid architecture (Mac Studio + Rubin GPU) is designed to exploit exactly this price/performance cliff.

03

Open models hit top tier

GLM-5.1 and Qwen 3.6 now rank globally competitive on agentic coding benchmarks. Zero licensing cost. Full infrastructure control. The ecosystem is ready.

The investment thesis.

RecordorAI is building the memory layer for AI agents โ€” a category that doesn't exist yet but will be foundational to every AI product built in the next decade.

Category creation, not capture. We're not competing in an existing market. We're defining the infrastructure layer that makes persistent-memory AI agents viable at consumer price points.
Factory model = multiple exits. Most vertical SaaS companies exit once. RecordorAI builds multiple companies on one infrastructure base โ€” each exit is incremental, not a binary bet.
Recurring revenue + exits. Infrastructure MRR is the compounding base. Company exits are the upside. These are not mutually exclusive.
Real customer, real problem. The memory wall is not theoretical. Every developer building multi-session AI agents hits it. RecordorAI solves it today.
Seed Round โ€” 2026
Raise$400,000
Equity25%
Pre-money$1.2M
Post-money$1.6M
Founder ownership75%
Use of Funds
Hardware (Mac Studio + Rubin GPU)$176K
12-month colocation$60K
Software + admin$38.4K
Founder expenses (12 mo)$120K
$50K already committed by founder

Build your audience.
We handle what they forget.

If you make videos about AI tools, build AI products, or teach developers how to ship โ€” RecordorAI is built for the kind of persistent, multi-session AI workflows that make great content and great products.

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YouTube Creators

Build AI demos and tutorials that actually remember context across episodes. No more re-explaining your AI's setup in every video. Use RecordorAI to build agents that carry state across sessions โ€” perfect for ongoing AI series.

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Developer Influencers

Ship AI-powered tools and products without rebuilding memory from scratch every time. RecordorAI gives your audience a memory backend they can actually use in their own projects.

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Educators & Researchers

Build AI tutors and research assistants that remember each student's progress across weeks. RecordorAI's memory layer makes long-horizon AI education workflows tractable for the first time.

Creator Program Benefits
๐Ÿ”“ Extended free tier access
๐Ÿ“น YouTube partnership opportunities
๐Ÿ’ฌ Direct access to the RecordorAI team
๐Ÿš€ Early access to new features
๐Ÿงช Dedicated API sandbox environment
๐ŸŽ Custom integration support for your projects

Brand assets & downloads.

Official assets for journalists, partners, and collaborators.

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Pitch Deck

Full investor presentation โ€” problem, solution, market, business model, factory model, and investment terms.

View Online โ†’
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Brand Guidelines

Logo usage, color palette, typography, and brand voice for RecordorAI.

View Guidelines โ†’
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One-Pager

Single-page summary of RecordorAI โ€” product, market, team, and investment highlights. Print-friendly.

View One-Pager โ†’

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