Store, Observe, Learn

The context data platform for production agents

Multi-modal Storage·Task Monitoring·Pattern Learning

Identify successful execution patterns through the Store → Observe → Learn → Act loop, so agents act smarter and succeed more over time.

Cloud Platform

Open source

Acontext PlatformContext Data Platform for AI Agents
💾
Store
Context storage & editing
📊
Observe
Task monitoring & metrics
🧠
Learn
Experience & skills
Context Storage Architecture┌─[ACONTEXT]─────[Store Context]
# Upload and store artifacts
artifact = client.disks.artifacts.upsert(
    disk.id,
    file=file,
    file_path="/documents/2024/"
)
# Step 1: Create a Space for skill learning
space = client.spaces.create()
print(f"Created Space: {space.id}")
# Step 2: Create a session attached to the space
session = client.sessions.create(
    space_id=space.id
)
# Store messages from any provider
client.sessions.store_message(
    session_id="abc-123",
    blob={"role": "user", "content": "Hello"},
    format="openai"
)
📦
ArtifactsFiles & outputs
🗂️
SpacesKnowledge bases
💬
SessionsConversation threads
Unified storage for all agent context
Task Monitoring & Observability┌─[ACONTEXT]─────[Get Tasks]
# Get extracted tasks from session
tasks = client.sessions.get_tasks(
    session_id="abc-123"
)
# Returns: Task list with status, progress
Task #1: Search iPhone news
Completed and reported
SUCCESS
Task #2: Initialize project
Waiting for approval
PENDING
Task #3: Deploy landing page
Not started
PENDING
Track agent tasks in real-time
Experience Learning & Skills┌─[ACONTEXT]─────[Search Skills]
# Search skills from Space
result = client.spaces.experience_search(
    space_id="space-123",
    query="authentication",
    mode="agentic"
)
# Returns: Relevant SOPs and skills
🔍
ExtractSOP
💾
StoreSkills
📖
SearchReuse
✅
Successful SessionTask completed with user approval
Learn from successful experiences
Dashboard & Analytics94.2%
Success Rate
1,234
Total Tasks
1.2s
Avg Latency
Monitor agent performance in real-time
[ ACONTEXT ]
Build AI agents that learn and improve
💾
Store
📊
Observe
🧠
Learn
📈
Dashboard
Get Started →

Context Data Platform for Self-learning Agents

Everything you need to build, deploy, and scale production-ready AI agents

Experience

Capture and analyze successful agent tool-calling chain, and dynamically injects only the most relevant context into agents

Context Engineering

Reduction, Compression, Offloading, Claude skills …… all in one backend

Artifact Disk

Filesystem-like workspace to store and share multi-modal outputs (.md, code, reports), ready for multiple agents collaboration.

Open Source

Architecture built on community standards. Every major dependency has a direct open-source alternative to ensure stack portability.

Multimodal Context Storage

Unified, persistent storage for all agent data, eliminating fragmented backends (DB, S3, Redis).

Background Observer

An intelligent scratchpad for long-running tasks, trace agent status and success rates in real-time.

SDKs & Integrations

Ready to use with OpenAI, Anthropic, LangGraph, Agno, and other popular agent frameworks

Join the Community

Connect with early builders & preview new features

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