We build MCP powered and agent-to-agent AI systems that share context, coordinate decisions, and execute complex workflows autonomously across your tools and infrastructure.
Moving beyond isolated chatbots to persistent, stateful, and collaborative systems.
The "Shared Memory" layer. MCP allows different AI agents to access the same documents, database records, and user history securely. No more copying and pasting context between windows.
The "Collaboration" layer. Specialized agents (Researcher, Coder, Reviewer) pass tasks to one another. They coordinate, critique, and execute complex workflows autonomously.
MCP servers run securely within your infrastructure. They index your documents and databases into vector stores that agents can query in milliseconds.
Granular control. The "Sales Agent" can read the CRM but can't delete records. The "Admin Agent" has full write access. You define the rules.
When a customer updates their profile in your app, the "Support Agent" knows immediately. No re-training or manual file uploads required.
Receives the complex request (e.g., "Analyze Q3 competitors") and breaks it down into sub-tasks.
Researcher: Scrapes the web.
Analyst: Reads the CSV data.
Writer: Drafts the summary.
Validates the output against guidelines. If it fails, it sends it back to the Writer for revision automatically.
Where context-aware agents create the most value.
An "Observer Agent" watches server logs. When an error spikes, it wakes the "Engineer Agent" who reads the stack trace, checks the git commit history via MCP, identifies the bad code, and even drafts a fix PR.
Continuously monitors LinkedIn and News APIs for trigger events. It searches Salesforce (via MCP) to check if they are a client, and if not, drafts a hyper-personalized email for the AE.
Upload a 100-page RFP. The orchestrator assigns sections to different agents: "Technical" reads the engineering docs, "Legal" checks compliance, and "Pricing" calculates costs.
Monitors weather/port data. If a delay is detected, the agent checks inventory levels in the ERP (MCP) and automatically re-routes shipments or notifies customers.
We audit your data sources (APIs, Databases, Docs) to define the schema.
We design specialized personas (Coder, Writer) with specific tools.
Building the routing rules: Who handles what? When to escalate?
Launch securely. We set up logging to monitor agent decisions.
Where context-aware agents create the most value.
Agents that monitor logs, detect anomalies (Context), and autonomously spin up new servers or rollback deployments (Action).
Connect Slack, Google Drive, and Notion into one MCP brain. Agents answer questions citing specific internal documents instantly.
One agent reads the invoice, another checks the budget in ERP, a third drafts the approval email for the manager.
From MCP-based context sharing to A2A execution systems, we turn complex requirements into production-ready AI solutions.