01
Shared Memory Layer
Agents access a unified knowledge base in real time, so a fact learned by one agent is immediately available to the rest of the system.
Advanced AI Architecture with Memory SystemsMulti-agent AI
Multi-agent AI
with advanced memory.
Intelligent agents with shared memory and context persistence.
Our multi-agent systems feature specialized AI agents that share memory, learn from interactions, and maintain context across sessions. Unlike simple chatbots, our agents leverage a multi-layer memory architecture combining short-term working memory, long-term knowledge storage, and episodic memory, enabling them to remember, learn, and collaborate intelligently.
- Live multi-agent systems
- 4
- Live multi-agent systems
- Documents indexed
- 156K+
- Documents indexed
- Transcription confidence
- 99.1%
- Transcription confidence
- Compliance verified
- 100%
- Compliance verified
Capabilities
What makes them more than chatbots
Memory, persistence and a second pair of eyes on every answer.
02
Context Persistence
Conversation history is maintained across sessions, so the system picks up where it left off instead of starting cold every time.
03
Adaptive Learning
Agents learn from past interactions and improve over time, tuning their behaviour against what actually worked.
04
Verification Before Delivery
A second agent reviews the first before anything reaches a customer, a clinician or a record, which is what makes these systems safe to ship.
How it works
Multi-agent architecture patterns
Four ways we wire agents together, chosen by what the workflow actually needs.
- 01
Sequential Processing
Agent A processes data, Agent B analyzes patterns, Agent C generates insights. Used for the clinical data pipeline in healthcare platforms.
- 02
Parallel Processing
Multiple agents work simultaneously on different aspects and the results are merged. Used for document analysis across multiple legal frameworks.
- 03
Hierarchical Delegation
A lead agent delegates subtasks to specialist agents based on requirements. Used for RFP generation with research, writing, and review agents.
- 04
Verification & Validation
An answer agent generates the response and a verifier agent checks accuracy and compliance. Used for medical or legal advice requiring double-checking.
In production
Production multi-agent AI delivering results
From healthcare to legal to e-commerce, our multi-agent architectures solve complex problems that single AI models cannot handle alone.
The stack
Built on a stack we run in production
The same tools across every build, so the system your team inherits is one we already operate.
- Framework
LangChain
CrewAI
AutoGen- Observability
LangFuse
Weights & Biases
- LLM
OpenAIAnthropic
GeminiGroq
- MCP
MCP Servers- Vector DB
Pinecone
WeaviateQdrant
ChromaDB
- Queue
Celery
RabbitMQ- Cache
Redis- Backend
FastAPI
Python- Database
MongoDB
PostgreSQL
Next step
Ready to Deploy Multi-Agent AI?
Build sophisticated AI systems with specialized agents working collaboratively. Schedule a consultation to discuss your complex workflow requirements.