Prime: Agent Memory Engine shipped
Time-travelyourdata
Query any point in history. Replay any sequence. Give your AI agents perfect memory. The temporal intelligence platform for event-driven applications.
Open source · MIT licensed · Self-host or cloud
The Problem
State Amnesia
Traditional databases only store current state. When something goes wrong, you can't see how you got there. No history means no answers, no audit trail, and no ability to replay or debug.
Temporal Blindness
Time-based queries are afterthoughts. Want to know what your data looked like last Tuesday at 3pm? Good luck. Most systems weren't built for time-travel, and retrofitting is painful.
AI Integration Gap
Your data is trapped behind rigid APIs. AI agents can't easily explore, analyze, or manage your event streams. The tools that exist weren't designed for autonomous workflows.
The Solution
AllSource combines high-performance event sourcing with AI-native tooling. Rust for speed, Go for orchestration, Elixir for distributed queries. The right tool for each job.
Immutable Event Log
Every change is captured as an immutable event. Complete audit trails, perfect reproducibility, and the ability to reconstruct any past state with time-travel queries.
Sub-Microsecond Queries
11.9μs p99 query latency with Parquet columnar storage. Lock-free data structures and zero-cost field access deliver real-time analytics at scale.
AI-Native by Design
27-tool MCP Server for Claude Desktop. AI agents can manage events, run analytics, detect anomalies, and orchestrate complex workflows autonomously.
Stream Processing Pipelines
Filter, Map, Reduce, Window, Branch, Enrich. Build real-time pipelines with a fluent API. Process 469K events/sec with the Rust core engine.
How It Works
Temporal Intelligence
Event Intelligence
Built in Rust for performance. Designed for AI agents. Every feature accessible through 27 MCP tools — let Claude or GPT manage your event streams autonomously.
Time-Travel Queries
Reconstruct any entity's state at any point in time with as_of queries. Debug issues, audit changes, or replay historical states instantly.
Microsecond Latency
11.9μs p99 query latency with Parquet-based storage. Optimized for both high-throughput ingestion and fast analytical queries.
Event Replay
Rebuild projections, fix incorrect state, or migrate data by replaying events. Filter by entity, type, or time range.
Projections
Materialized views that update automatically. Entity snapshots, counters, time series, funnels, and custom projections.
Schema Registry
Versioned schemas with backward, forward, and full compatibility modes. Validate events at ingestion time.
Multi-Tenant Isolation
Every event, projection, and query is scoped to a tenant. RBAC with 4 roles and configurable quotas per tier.
Event Sourcing
- Immutable audit logs
- State reconstruction
- Event replay
AI Workflows
- 27 MCP tools
- Claude integration
- Autonomous agents
Analytics
- Stream processing
- Real-time pipelines
- Correlation analysis
Pricing
FREE
$0/ month
billed monthly
- 10K events/month
- 1 GB storage
- 1K queries/hour
- 2 API keys
- 5 projections
- Community support
Get API Key
Perfect for side projects and learning
PRO
$29/ month
billed monthly
- 500K events/month
- 10 GB storage
- 50K queries/hour
- 10 API keys
- 25 projections
- MCP server access
- Priority support
Get API Key
For developers shipping production apps
TEAM
$99/ month
billed monthly
- 5M events/month
- 100 GB storage
- Unlimited queries
- Unlimited API keys
- Unlimited projections
- MCP server access
- Dedicated support
Get API Key
For growing teams building at scale
FAQ
Blog
Tiered Context Loading: Cut Agent Memory Costs by 60% Without Losing Recall
Most agent turns don't need full recall. L0/L1/L2 tiers let agent loops fetch exactly the context depth they need — from 100-token stats to full hybrid retrieval — reducing token costs while keeping accuracy where it matters.
12μs Agent Memory: How We Got There
From event store to agent memory engine in microseconds. DashMap projections, HNSW vector index, and why the storage layer matters more than the query layer.
Building Agent Memory in Rust: From Event Store to Knowledge Graph
How we built a unified agent memory engine — vectors + graph + compressed index — on top of an event store. Architecture decisions, SOLID refactoring, and why Rust was the right choice.
How a Compressed Index Doubles Cross-Domain Recall
Vector similarity finds X or Y — rarely both. A 500-token markdown index bridges the gap. Here's why, with benchmark data.
From zer0dex to AllSource: What We Learned
We analyzed zer0dex's dual-layer memory system, found the insight that matters, and built on it. Here's what we kept, what we changed, and why.
zer0dex vs AllSource: What Agent Memory Actually Needs
zer0dex proved that a compressed index doubles cross-domain recall. We took that idea, made it automatic, and added temporal reasoning. Here's the honest comparison.
Your AI Agents Need Memory, Not Just Storage
AI agents are getting smarter, but they still can't remember yesterday. Here's why temporal context is the missing piece in agentic AI.
Event Store vs Database: Choosing the Right Foundation
Databases store state. Event stores store history. Here's how to decide which foundation your application actually needs.
Temporal AI: Why Your RAG Pipeline Needs a Timeline
Vector search finds similar content. Event sourcing tracks history. Combined, they create AI that truly understands context.
Why Event Sourcing in 2026: Beyond Simple Storage
Your application needs more than a database—it needs perfect memory. Here's why event sourcing matters more than ever.
AI Agents with MCP Tools
How to let Claude and other AI agents manage your event streams autonomously.
Time-Travel Queries Explained
How to reconstruct any entity's state at any point in time with all.source.
Introducing all.source
Time-travel your data with the AI-native event store built for the future.
Give your application perfect memory
No credit card required. 10K events/month free.