Agent Memory Infrastructure

blink / Long-term memory for AI agents.

Sub-millisecond graph recall. 70% lower prompt costs. Built-in knowledge graph with zero extra LLM write fees.

Start Free → Migrate from Mem0 → The Breakthrough

$ uv add blink-memory

1.8 ms recall

1 / 387 Save Time (1.8 ms)

1 / 3.7 Tokens (70% cut)

1 / 133 Memory (90 MB)

Drop-in memory for

LangGraph OpenAI Agents Claude Code Cursor & Windsurf CrewAI 1-Line Mem0 / Zep Swap

The Fractional Advantage

State-of-the-art recall. A fraction of the cost.

blink / compiles raw conversation streams into neural state in a single pass.

01 · Fraction of Time

1 / 387 write time

1.8 ms saves · 387x faster ingest

Ingest 100K tokens in 67 seconds with zero background queue lag.

blink / 67 sec · 1,475 tok/s

Mem0 / Zep 4.6 hrs · 6 tok/s

02 · Fraction of Cost

1 / 3.7 token spend

Zero LLM save fees · 70% token cut

Retrieve lean neural context that cuts downstream prompt bills by 3.7x.

blink / 0 LLM calls · 27% tokens

Mem0 / Zep 2–4 LLM calls · 100% tokens

03 · Fraction of Space

1 / 133 RAM space

90 MB core vs. 12 GB stack

Store 100K tokens of active state in 90 MB RAM with zero vector DB containers.

blink / 90 MB RAM

Mem0 / Zep 12,000 MB (12 GB)

The Innovation

How blink / eliminates the LLM extraction bottleneck.

Why legacy agent memory requires 4 glued microservices and costs $0.03/write—while blink / compiles state directly in a single 1.8 ms pass.

⚠ Legacy 4-Service Stack (Mem0, Zep, LangMem)

Chained LLM Prompts & Glued Databases

Every write invokes an external LLM to extract JSON entities, runs an embedding model, and persists across two database containers.

1. Agent Message Stream HTTP Network Hop

↓ payload latency & TLS handshake

2. LLM Fact Extractor (GPT-4o) 2,500 ms · $0.03/write

↓ JSON schema parsing & retries

3. Embedding Model (text-embedding-3) 250 ms · token bill

↓ multi-container dual-write

4. Vector DB + Graph DB (Qdrant & Neo4j) 12,000 MB RAM · Docker

Write Latency 2,500 ms

Write Cost $0.030 / req

RAM Required 12,000 MB

⚡ blink / Direct Neural State Core

Single-Pass Compiled State Graph

Token streams compile directly into a dynamic topological graph via native state projection in Rust/C-FFI. Zero LLM write calls.

1. Agent Message Stream Direct In-Process Stream

↓ zero network hop · memory bus speed

2. Single-Pass State Projection 1,475 tok/s · $0.000 (0 LLM)

↓ compiled native neural kernel

3. Recurrent Knowledge Graph Self-Pruning · 1.8 ms recall

↓ L1/L2 cache resident execution

4. Embedded Rust Core Binary 90 MB RAM · Zero Containers

Write Latency 1.8 ms (387x)

Write Cost $0.000 (0 LLM fees)

RAM Required 90 MB (133x)

01 / ZERO-LLM EXTRACTION

Neural State Compilation

Instead of spending $30 per 1,000 writes prompting an LLM to extract JSON entities, blink / passes token streams through compiled state kernels. Extraction happens during raw ingestion at 1,475 tok/s with zero LLM API bills.

02 / COMPACT REPRESENTATION

Ultra-Dense Neural States

Powered by FractionML's high-density state compression architecture. Working representations pack into cache-aligned discrete states, fitting 100K active tokens into just 90 MB RAM without external vector database clusters.

03 / DYNAMIC TOPOLOGY

Living Recurrent Graph

Vector databases blindly store raw text chunks that collide and hallucinate. blink / maintains an evolving topological graph where obsolete facts are pruned, contradictory statements reconcile, and multi-hop associations link automatically.

04 / DETERMINISTIC CORE

Sub-2ms Rust Engine

Engineered from scratch in Rust with zero runtime allocations on the query path. Traversal and recall execute directly in L1/L2 cache in 1.8 ms. Runs 100% locally with zero outbound telemetry, ensuring complete data privacy and sovereignty.

How It Works

One neural core replaces four glued services.

Drop blink / into your agent or IDE in three lines of code.

Continuous Memory Across Months of Sessions

Stream multi-session conversations at 1,475 tok/s with zero LLM write fees and 1.8 ms multi-hop recall.

1-Line Drop-In Replacement for Mem0

Keep your existing .add() and .search() calls while cutting memory infrastructure RAM by 133x. View 60s Migration Guide →

Behavioral Code & Bug Localization

Index AST control-flow and state mutations natively for 100% bug localization on complex codebases.

SOTA Benchmarks

Outperforming Hindsight, Zep, and Mem0 across every horizon.

Higher accuracy on conversational (LoCoMo) and 10M-token long-horizon (BEAM) benchmarks—at a fraction of the time, cost, and space.

Conversational Recall

LoCoMo Accuracy (%)

95.3% SOTA

blink / frontier

95.3%

blink / base

89.9%

Honcho

89.0%

Hindsight

85.6%

Zep

75.1%

Mem0

66.9%

Extreme Long-Horizon Memory

BEAM (100K → 10M Tokens)

Only Engine @ 10M

blink / @ 100K

86.5%

Hindsight @ 100K

66.2%

Mem0 @ 100K

35.9%

blink / @ 10M

72.4%

RAG Baseline @ 10M

23.4%

Mem0 / Zep @ 10M

OOM / DNF

Memory Engine	LoCoMo	BEAM 100K	BEAM 10M	Write Speed	Write LLM Calls	RAM @ 100K
blink / frontier SOTA	95.3%	86.5%	72.4%	1,475 tok/s (67s)	0 ($0)	90 MB
blink / base Open Core	89.9%	80.1%	63.5%	1,475 tok/s (67s)	0 ($0)	90 MB
Hindsight	85.6%	66.2%	OOM / DNF	LLM-bound	Every write	Multi-GB
Zep	75.1%	—	OOM / DNF	LLM + Graph bound	2–4 calls/turn	Graph + Vector DB
Mem0	66.9%	35.9%	OOM / DNF	6 tok/s (4.6 hrs)	Every write	12,000 MB (12 GB)

Deployment & Pricing

Run locally for free. Scale on Cloud or private VPC.

No hidden OpenAI fees to save memories. No $249 graph paywalls. Full relational memory included from $15/mo.

Local Open Core

blink / local*

$0 / forever local

For developers, Claude Code, Cursor & offline agents.

180 MB Rust runtime · 0 PyTorch overhead
Unlimited local tokens · 10M+ context horizon
Instant local saves (1.8 ms) · Zero rate limits
Local Entity & AST Graphs · Included free ($0 paywall)
Apache 2.0 SDK, CLI & MCP server

blink / pro

$15 / month base

No $249 Graph Paywall

Full neural memory for production agents & startups.

100,000 ops / mo included ($0.15/1k ops effective)
Graph & Relational Memory · Included ($0 paywall, vs Mem0 $249)
Dedicated agent workspace · Zero cross-talk
Code AST & symbol graphs · Fast semantic recall
Pay-as-you-go overage only · $0.50 / 1k queries

Scale & Teams

blink / platform

$210 / month base

High-throughput multi-tenant memory infrastructure.

1,500,000 req / mo included ($0.14 / 1k req)
50 isolated tenant workspaces with instant hot-swapping
66.6 QPS pooled concurrency · Dedicated burst lane
Instant GDPR unlearning (6.41 ms surgical rollback)
Volume overage · $0.20 / 1k req

Private VPC · Air-Gapped

blink / enterprise

Custom / dedicated VPC

Dedicated Brain Appliance inside your own VPC or on-prem.

Multimodal vision & document state (Exclusive)
Dedicated Brain Appliance inside customer VPC
100% data sovereignty · Zero outbound calls
Air-gapped deployment · FedRAMP / HIPAA ready
Custom domain adaptation & 99.99% SLA

*blink / local SDK + MCP is Apache 2.0. The local neural-core binary is free for personal and evaluation use. Base cloud subscriptions include monthly operations; pay-as-you-go applies strictly to overages with zero hidden platform fees.

The $249 Graph Paywall

Why pay Mem0 $249/mo just to unlock Graph Memory?

Mem0 locks relational entity graphs behind a $249/mo Pro paywall and charges for every slow OpenAI extraction call. blink / compiles multi-hop graphs natively in 1.8 ms with $0 extra LLM fees—included standard in blink / pro for $15/mo (saving you $2,808/yr).

blink / pro $15 / mo ✅ Full Graph Memory Included · 1.8 ms · $0 extra LLM fee

Mem0 Pro $249 / mo ❌ Graph locked behind $249 paywall + extra OpenAI fees per save

16.6× Cheaper Base · $2,808/yr Saved

Migrate from Mem0 in 60s →

Head-to-Head Comparison

The True Cost of Agent Memory: Blink vs. Mem0 & Zep

See why engineering teams are abandoning $249/mo graph paywalls and rate-limited LLM extraction wrappers.

Capability / Metric	blink / pro Ours	Mem0 Starter	Mem0 Pro	Zep Flex
Monthly Base Price	$15 / mo	$19 / mo	$249 / mo	$125 / mo
Graph & Relational Memory	✅ Included ($0 paywall)	❌ Locked ($249 paywall)	Included ($249/mo)	Partial (Graphiti add-on)
Multi-Hop Fact Traversal	1.8 ms (Native neural graph)	❌ Unsupported (Vector only)	15–30 sec (LLM triple synthesis)	5–20 sec (Graphiti async)
Time & Cost to Save a Memory	1.8 ms · $0 extra LLM fee	15–30s · Extra OpenAI fees per save	15–30s · 3–5 OpenAI calls per save	5–20s · Background worker fees
Included Operations	100,000 ops	50,000 ops	500,000 ops	50,000 credits
Code AST & Symbol Graphs	Full AST & Call Graphs	❌ Text only	❌ Text only	❌ Text only
Recall Accuracy @ 10M+ Tokens	72.4% (Zero drift)	48.6% (Vector collapse)	52.1% (Synthesis loss)	54.3% (Temporal fading)
Multimodal Vision State	Enterprise tier only	❌ No	❌ No	❌ No
Overage Model	Gentle PAYG: $0.50 / 1k queries	Hard cap / Forced upgrade	Enterprise upsell	$2.50 / 1k ops ($25/10k)

*Mem0 locks relational and entity graph memory behind their $249/mo Pro plan, triggering external LLM extraction prompts every time you save a memory. Blink Pro includes native relational graph memory, entity associations, and code AST call graphs out of the box for $15/mo with zero extra LLM fees. Multimodal vision state is exclusive to Blink Enterprise.

Customer FAQ

Frequently Asked Questions

Everything you need to know about giving your AI agents persistent, real-time memory with blink /.

Q How does Blink achieve instant 1.8 ms saves without extra LLM API bills?

Blink processes conversation turns and documents directly into our 90 MB local neural core at 1,475 tokens/second. You gain instant real-time memory with zero queue lag and zero added token bills.

Q What does native Graph & Relational Memory enable my agents to do?

Graph Memory connects entities, user preferences, and code relationships across months of sessions. Your agents gain multi-hop reasoning, cross-session continuity, and zero-drift recall out of the box.

Q How does Blink cut prompt token costs by 70%?

Instead of dumping raw transcript logs into prompts, Blink synthesizes dense neural states and extracts only high-precision relevant facts. This cuts downstream prompt payloads by 3.7x, accelerating inference and slashing your token bills.

Q Can I drop Blink into an existing agent stack without refactoring?

Yes, Blink provides drop-in compatibility with standard .add() and .search() calls. You can replace your existing memory import in one line and keep your entire LangGraph, CrewAI, or agent architecture intact.

Q What are my data privacy, sovereignty, and hosting options?

Blink Local runs 100% locally on your machine with zero outbound network traffic. For cloud or enterprise, you can choose isolated encrypted cloud workspaces or run directly inside your own private VPC.

Q What happens if my agent workload scales past 100,000 monthly operations?

Your agents never experience downtime or rate limiting. Any usage beyond your monthly allowance continues seamlessly at a flat pay-as-you-go rate of $0.50 per 1,000 operations.

Start in a blink /

Run locally for free right now with blink / local*, start on blink / pro ($15/mo), or deploy blink / enterprise on your VPC.

blink / local* ($0)

Install in one command

$ uv add blink-memory $ npx -y @fractionml/blink-mcp --init

blink / pro ($15) & enterprise

Request an API key

Direct: thanh@fractionml.com