Move Beyond AI Pilots to Production-Scale Intelligence.

AI orchestration is the coordinated management of multiple AI agents, data sources, and enterprise systems to achieve complex business goals reliably and at scale. Without orchestration, AI initiatives remain isolated pilots, each model operating independently, unable to access the full context of your business data or trigger actions across systems. Orchestration is what transforms individual AI capabilities into an integrated, production-grade intelligence layer that actually runs your business processes.

Model Context Protocol (MCP) is an open standard developed by Anthropic that provides a universal way for AI models to interact with external data sources and tools. Instead of building custom integrations for every system your AI needs to access, MCP creates a single, standardized interface. Mirketa uses MCP to expose your enterprise systems, CRM, ERP, legacy databases, and APIs, as AI-accessible Resources (for reading context) and Tools (for executing actions). This eliminates the M × N integration complexity and makes your entire data estate available to AI agents through one governed layer.

Absolutely not, and this is one of our core differentiators. We have never required a client to replace their legacy systems to implement AI orchestration. Our MCP integration layer is designed to connect to existing infrastructure, exposing legacy databases and applications as secure, AI-readable resources. Whether your systems are decades-old mainframes or modern SaaS platforms, our architecture adapts to what you have, not the other way around. The value of your existing data and workflows is preserved and amplified, not discarded.

Our Trust & Security Layer is built into every orchestration deployment. It operates on three principles: Approval Gates require explicit human consent before any consequential action such as financial transactions, record modifications, or customer communications. Ambiguity Resolution ensures that when an agent reaches a confidence threshold below a defined level, it escalates to your team with structured options rather than guessing. Trust Calibration starts every deployment with maximum human oversight and progressively reduces approval friction only as the system demonstrates consistent, validated performance. You remain in control at every stage.

Our standard delivery timeline runs 8–10 weeks from initial Architecture Assessment to production launch. Week 1–2 covers the assessment and opportunity identification. Week 2–3 is dedicated to framework design and security architecture. Weeks 3–8 involve the build, integration, and iterative testing cycle. Weeks 8–10+ cover production deployment, team training, and performance optimization. Complex enterprise environments with many legacy systems may require additional time, but our pre-built accelerators and MCP integration framework consistently reduce delivery timelines by 40% compared to custom-built approaches.

Yes, Salesforce and Agentforce are among our deepest integration competencies. We are a Salesforce partner with extensive experience deploying Einstein AI, Agentforce, and Data Cloud. Our orchestration frameworks are designed to work natively within the Salesforce ecosystem, connecting Agentforce agents to your external systems, legacy databases, and non-Salesforce platforms through our MCP integration layer. This means your Salesforce investment becomes the orchestration hub for your entire enterprise AI strategy, not just a CRM.

You do: 100%. While we leverage our pre-built accelerators and frameworks to speed up delivery, the underlying intellectual property developed during your engagement belongs entirely to your organization. This is a non-negotiable principle for us. We believe that the AI systems running your business should be owned by your business, not licensed from a consulting firm. Our accelerators reduce your time-to-value; your custom orchestration layer is yours to own, operate, and evolve independently.