The Problem
AI agents hit a memory wall — not a model wall.
- Context windows are expensive and ephemeral — wiped at the end of each session
- Memory doesn't survive across sessions — OpenAI and Anthropic are built for single conversations
- Inference cost compounds with history — at 10K MAU, naive API approaches run $75–180K/mo in closed-provider fees
- Data stays on third-party infrastructure — enterprises can't accept that
The Solution
Three-tier memory architecture. Built for agents that work.
⚡ Hot
GPU KV Cache — 5–10K tokens in GPU VRAM, instant recall. $0.003/1K tokens — 800x cheaper than GPT-5.4.
🔍 Warm
Semantic Vector Store — Full history in pgvector + Supabase. Infinite retention, queried on demand.
🧠 Cold
Entity Compression — ~500 tokens per entity. Extractive, not generative. No hallucination risk.
Product
API + SDK + Chat UI. Works with your stack.
REST API — Python + JavaScript SDKs. Drop-in for LangChain, AutoGPT, CrewAI.
Model Routing — Auto-select Gemma 4 (fast) vs GLM-5.1 (deep) by task complexity.
Chat UI — Browser-based, connected to same memory layer. Auto benefits from tiered memory.
SOC 2 + HIPAA — Supabase certified. Customer data isolated in dedicated partitions.
Open Stack — vLLM, pgvector, Supabase. No vendor lock-in.
Webhooks — Memory events stream in real time. Build reactive workflows on top.
Market
$42B
AI Agent Platforms TAM (2026)
65%
CAGR (Developer AI APIs)
$15B
Long-context AI tools by 2030
Source: Gartner, Forrester, IDC 2026
Business Model
Simple tiers. Recurring revenue. Real margin.
Developer
$15/mo
50K tokens/day · REST API · Chat UI
Pro
$75/mo
500K tokens/day · All models · 10 agents
Premium
$175/mo
2M tokens/day · 50 agents · Advanced analytics
Enterprise
Custom
Unlimited · Dedicated infra · SLA
Monthly burn$24,250
Cost per user$4.23/mo
Revenue per user$15/mo
Gross margin72%
Break-even~2,500 MAU → $30K/mo
Competition
No royalties. Own your infrastructure.
| RecordorAI | OpenAI | Anthropic | |
|---|---|---|---|
| Token royalties | $0 — Apache 2.0 | $2.50–$15/M | $5–$25/M |
| Context window | 200K + tiered | 200K | 200K |
| Cross-session memory | Yes | No | No |
| Own inference infra | Yes | No | No |
At 10K MAU, closed providers: ~$75–180K/mo. RecordorAI: ~$14K/mo. 5–10x permanent cost advantage.
Timing
The window opens H2 2026.
01
NVIDIA Vera Rubin (H2 2026) — 10x inference throughput per watt, 1/10th cost/token vs Blackwell.
02
Apple M5 Mac Studio (H2 2026)— Workstation-tier inference becomes real. RecordorAI's hybrid architecture exploits this.
03
Open models hit top tier — GLM-5.1 and Qwen 3.6 globally competitive. Zero licensing cost. Full infrastructure control.
Company Factory
One platform. Multiple businesses.
RecordorAI infrastructure hosts both its core inference business and a pipeline of vertical SaaS companies — built using A.L.I.C.E. and sold to larger players in each space. RecordorAI retains the infrastructure contract post-sale.
Companies BuiltPlatform MRRInfra ValueExit ValueTotal
1 company$150K/mo$1.5M$2–5M$3.5–6.5M
5 companies$750K/mo$7.5M$10–25M$17.5–32.5M
10+ companies$1.5M/mo$15M$20–50M$35–65M