The Technologies Develo Builds With

AWS — our cloud foundation

Everything Develo ships runs on AWS: containers (ECS/EKS) for applications, managed databases (RDS, DynamoDB, ElastiCache), S3 for data and artifacts, Lambda for event-driven work, CloudFront and Route 53 at the edge, and CloudWatch for monitoring. Our CI/CD pipelines deploy from source control on every change, with IaC for reproducible environments.

Amazon Bedrock — hosted LLMs in the enterprise

We run large language models through Amazon Bedrock: access to frontier models (Anthropic Claude, Llama and others) inside your own AWS tenancy, with data controls, guardrails and pay-per-use economics. Bedrock's knowledge bases and prompt management let us build RAG pipelines and governed prompt libraries without leaving the cloud.

Autonomous AI agents

Our flagship engineering focus is autonomous agents: systems that perceive context, plan, call tools, observe results and act toward a goal. We build the full agent stack — planning loops, memory, tool definitions, guardrails, evaluation harnesses and human-in-the-loop escalation — and orchestrate teams of specialized agents with supervisor patterns (see Develo Multi-Agent and AI Agents).

Model Context Protocol (MCP)

We adopt the Model Context Protocol (MCP), the open standard for connecting LLMs and AI agents to tools and data. With MCP servers, your CRM, order system or internal API becomes a governed, versioned tool that any model or agent can use — with scoped permissions, audit logs and no custom glue code per model. MCP is how we keep agent capabilities interoperable and auditable as the ecosystem evolves.

LLMs, RAG and fine-tuning

We treat model choice as an engineering decision, not a religious one. Most products combine: strong base prompts, Retrieval-Augmented Generation (RAG) over your documents and operational data (vector search, hybrid retrieval, reranking, citations), and — where prompting and retrieval plateau — LLM fine-tuning for domain tone, format and task accuracy. Every choice is validated with evaluation suites on real business cases.

Data & search layer

Vector databases and embedding pipelines give our systems semantic access to catalogs, documents and history; hybrid search (vector + keyword + structured filters) keeps retrieval reliable. Data pipelines sync your systems in near-real-time so agents always answer with current state.

How it fits together

Channels (WhatsApp / Marketplace / Web / API)
        ↓
AWS (ECS · RDS · S3 · CloudFront · CloudWatch)
        ↓
Develo AI Layer
   ├── Amazon Bedrock (LLMs + knowledge bases + guardrails)
   ├── Agents & orchestration (single-agent · multi-agent)
   ├── MCP servers → your systems (CRM · ERP · ecommerce · APIs)
   └── RAG / vector search / fine-tuned models
        ↓
Human operators (supervision, approval, takeover)

Explore our solutions