Our Agent Development Stack
Six distinct agent engineering capabilities, each built on the leading frameworks of 2026.
OpenAI Agents SDK & Swarm Systems
We build multi-agent systems using the OpenAI Agents SDK, the production-ready evolution of OpenAI Swarm. These systems orchestrate teams of GPT-4o and GPT-o3 agents that delegate tasks, enforce guardrails, and execute parallel workflows with full tracing via LangSmith.
- Multi-agent handoff orchestration
- Built-in guardrails & tracing
- Compatible with 100+ LLMs
Anthropic Claude Agent & MCP Integration
Using the Anthropic Claude Agent SDK alongside the Model Context Protocol (MCP), we build agents that natively connect to your live business tools like Notion, Salesforce, and internal APIs. Claude Opus 4.5 agents handle complex, multi-session workflows that previously required entire teams.
- Native MCP server connections
- Claude Opus 4.5 multi-session memory
- Slack, Asana & Jira integrations
LangGraph Stateful Agent Workflows
For complex, decision-tree workflows that require conditional logic and rollback capabilities, we engineer with LangGraph. Its graph-based execution model maintains explicit state over long-running processes, enabling agents to loop, retry, and adapt in real time across your enterprise systems.
- Stateful multi-step execution
- Conditional branching & retry logic
- Production deployment via LangGraph Cloud
CrewAI Role-Based Agent Teams
We design CrewAI multi-agent systems where distinct agents play specialized roles: Researcher, Analyst, Writer, and QA. This crew-based approach mirrors real team structures and is ideal for content pipelines, market research automation, and sales workflow orchestration.
- Role-based agent specialisation
- Parallel task execution
- Integration with LangChain tools
Google ADK & Vertex AI Agents
For enterprises within the Google Cloud ecosystem, we build with the Google Agent Development Kit (ADK) backed by Gemini 2.0 Flash and Gemini 2.0 Pro. ADK enables hierarchical agent compositions and custom tool execution at cloud scale via Vertex AI Agent Engine.
- Gemini 2.0 Pro / Flash models
- Vertex AI production deployment
- Hierarchical agent compositions
On-Premise & Private Cloud Agents
When data cannot leave your environment, we deploy agents using open-weight models like Llama 3.3 70B or Mistral Large 2 running on your own GPU infrastructure. Combined with a local Pinecone or pgvector RAG store, your agents operate completely air-gapped.
- Llama 3.3 & Mistral Large 2 deployment
- Local vector DB (pgvector / Qdrant)
- Zero data egress guarantee
SKILL.md Agentic Engineering
We lead the shift toward agentic competence with the 2026 SKILL.md open standard. By packaging workflows into modular, reusable skills, we ensure your agents are hyper-specialized, portable across frameworks, and context-efficient via progressive disclosure of expert knowledge.
- Standardized SKILL.md packaging
- Progressive disclosure architecture
- Cross-framework skill portability
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