Move Beyond AI Pilots
to Production-Scale Intelligence.
Architect secure, scalable AI ecosystems that unify your SaaS and legacy environments, without the cost or risk of system replacement. Powered by Agentic AI, MCP integration, and proven multi-agent frameworks.
Healthcare
Financial Services
Nonprofit
E-Commerce
Technology
Most AI Initiatives Stall Before They Scale
The bottleneck isn't intelligence it's orchestration. Enterprises get trapped building one-off integrations that create unsustainable complexity and unpredictable AI behavior.
Every new AI model or data source requires a hand-crafted adapter. As your AI portfolio grows, so does the complexity creating context bloat, context overflow, and unpredictable model behavior that makes production deployment nearly impossible.
- Bespoke adapters multiply with every new model or data source
- Context windows overflow, degrading AI response quality
- No consistent governance across AI agents and tools
- Legacy systems locked out of AI value creation
- Pilot projects fail to scale to production environments
Instead of building one-off integrations, we create a structured, reusable orchestration layer that connects AI models, enterprise tools, and legacy systems through a single, governed architecture making your AI initiatives scalable from day one.
- Single MCP integration layer replaces dozens of custom adapters
- Managed context windows prevent overflow and ensure accuracy
- Centralized governance with Approval Gates and Trust Calibration
- Legacy systems exposed as secure AI-accessible Resources and Tools
- Production-ready architecture from Week 1, not an afterthought
What We Build for Your Enterprise
Every capability is designed around a specific enterprise challenge not generic AI theory. Each one is production-ready, reusable, and built to integrate with your existing systems.
We utilize Anthropic's open standard to collapse complex integration surfaces into a single, shared protocol. One integration layer connects AI to every system CRM, ERP, databases, and legacy applications.
- Eliminates the M × N integration complexity permanently
- Exposes enterprise data as secure, AI-readable Resources
- Enables executable Tools for cross-system workflow automation
- Transport-agnostic: works via stdio, HTTP, and SSE protocols
We don't just deploy models we coordinate multiple AI agents, memory stores, and human touchpoints into reliable, long-running workflows. Complex tasks are decomposed and distributed across specialist agents for maximum precision.
- Orchestrator–Subagent patterns for complex task decomposition
- Parallel Fan-out to reduce total workflow latency
- DAG pipelines for sequential, dependency-aware processing
- Human-in-the-loop escalation for high-stakes decisions
Your legacy systems contain decades of business-critical data. We unlock that value by layering sophisticated AI orchestration directly onto your current infrastructure without migration, replacement, or disruption.
- CRM and legacy databases exposed as AI-accessible Resources
- Secure read/write access governed by enterprise policies
- Zero system replacement build on what you already own
- Bi-directional data flow between AI agents and legacy systems
Enterprise AI must be trustworthy before it can be transformative. Our Trust Layer implements progressive oversight starting with maximum human control and systematically reducing approval friction as the system demonstrates consistent, reliable performance.
- Approval Gates for financial transactions and record modifications
- Ambiguity Resolution: agents escalate with structured options, never guess
- Trust Calibration: oversight reduces as performance is validated
- Bounded retry logic prevents runaway agent loops
Architectural Patterns for Production AI
Three proven orchestration patterns that power reliable, scalable AI deployments each selected based on your specific workflow complexity and performance requirements.
A central orchestrator agent decomposes complex tasks and delegates to specialist subagents each optimized for a specific function. Results are aggregated and validated before returning to the user, ensuring precision at every step.
Multiple agents are spawned simultaneously across independent data streams, dramatically reducing total latency. Ideal for scenarios where tasks can be executed in parallel such as multi-source data retrieval or concurrent analysis across business units.
Sequential dependencies are modeled as a DAG, ensuring each processing step enriches the next in a controlled, auditable pipeline. Every node's output becomes the next node's context building intelligence progressively through the workflow.
Server Architecture
We expose your CRM and legacy databases as Resources (read-only context) and Tools (executable functions) through a secure, governed MCP interface that AI agents can query reliably.
Transport Flexibility
Whether via stdio for local developer tooling or HTTP + SSE for multi-tenant cloud environments, our architecture remains transport-agnostic adapting to your infrastructure, not the other way around.
Reliability Engineering
Bounded retry logic handles tool failures gracefully, while selective summarization prevents context overflow. Every component is built for production uptime, not just proof-of-concept demos.
AI Orchestration Across Every Vertical
Our orchestration frameworks are not generic they are designed around the specific data architectures, compliance requirements, and workflow patterns of each industry we serve.
Healthcare AI Orchestration
Healthcare organizations manage a fragmented mix of EHR systems, payer platforms, scheduling tools, and clinical databases. Our orchestration layer bridges these silos enabling AI agents to access patient data, trigger care workflows, and coordinate across clinical teams in real time, all within HIPAA-compliant governance frameworks.
- 50%+ Faster chart review with AI Patient Chart Summaries
- 40% Reduction in call center volume via Smart Appointment Agent
- 30-40% Fewer no-shows with predictive intervention workflows
- ↑ 25% First-pass claim acceptance via orchestrated pre-submission review
Financial Services AI Orchestration
Financial institutions operate across a complex web of core banking systems, compliance platforms, and customer-facing applications. Our orchestration layer enables AI agents to perform real-time fraud detection, automate compliance checks, and deliver personalized financial guidance all within strict regulatory governance frameworks.
- 60% Reduction in manual compliance review time
- 3x Faster fraud alert triage with multi-agent analysis
- 45% Improvement in customer query resolution speed
- ↓ 30% Operational cost reduction via workflow automation
Nonprofit & Education AI Orchestration
Nonprofits and educational institutions often operate with limited IT resources but complex stakeholder relationships. Our orchestration layer connects donor management systems, student information platforms, and fundraising tools enabling AI agents to drive engagement, predict churn, and optimize outreach at scale.
- 25% Higher donor retention through predictive engagement
- 40% Improvement in fundraising campaign ROI
- ↓ 50% Reduction in manual donor outreach effort
- 3x Faster grant application processing via AI workflows
Technology & SaaS AI Orchestration
Technology companies face unique challenges: rapid product iteration, complex DevOps pipelines, and high-velocity sales cycles. Our orchestration layer accelerates every stage from automated code review and deployment pipelines to AI-powered sales intelligence and customer success workflows.
- 35% Shorter DevOps cycle times via agentic automation
- 50% Reduction in mean time to remediate (MTTR) security issues
- 20-30% Improvement in sales pipeline conversion rates
- ↑ 40% Agent productivity with AI-powered case resolution
From Architecture Assessment to Go-Live in Weeks
Our proven delivery framework ensures every AI orchestration project is deployed with precision, speed, and measurable business impact not months of consulting engagements.
Evaluate your existing systems, data quality, integration landscape, and identify the highest-ROI orchestration opportunities for your specific business context.
Design the MCP integration layer, agent routing logic, data models, security protocols, and Trust Layer governance framework tailored to your enterprise policies.
Develop the orchestration hub, connect APIs and legacy databases, configure multi-agent workflows, and run iterative demos with your team throughout the build cycle.
Launch to production, train your teams, monitor agent performance in real time, and continuously optimize context windows and routing logic based on live outcomes.
Mirketa vs. Building In-House vs. Generic Platforms
Not all AI orchestration approaches are equal. Here is how our approach compares to the alternatives most enterprises consider.
| Capability | Mirketa Orchestration | Build In-House | Generic AI Platform |
|---|---|---|---|
| Time to production deployment | ✓ 8–10 weeks | 6–18 months | 3–6 months (with customization) |
| Legacy system integration | ✓ Zero replacement required | ~ Requires migration effort | ✗ Often requires system upgrade |
| MCP / open standard support | ✓ Native MCP integration | ~ Requires custom build | ~ Vendor-specific protocols |
| Enterprise Trust & Security Layer | ✓ Built-in, configurable | ~ Must be designed from scratch | ~ Basic governance only |
| Client IP ownership | ✓ 100% client-owned | ✓ Client-owned | ✗ Platform-dependent |
| Industry-specific use cases | ✓ Pre-built accelerators | ✗ Built from zero | ~ Generic templates only |
| Salesforce / Agentforce integration | ✓ Deep native integration | ~ Requires Salesforce expertise | ~ API-level only |
What Our Clients Say About AI Orchestration
"We were convinced we'd need to replace our legacy EHR system to participate in AI. Mirketa proved us wrong. Their MCP integration layer connected our existing systems to AI agents in weeks not the 18-month migration project we feared. We now have production AI workflows running on infrastructure we've had for years."
"What impressed us most was the Trust Layer. We were nervous about AI agents making autonomous decisions in our financial workflows. Mirketa's Approval Gates and Trust Calibration framework gave our compliance team the confidence to approve production deployment. The system started with maximum oversight and earned its autonomy over time."
You Have Questions. We Have Answers.
The most common questions we hear from enterprise leaders before starting their AI orchestration journey.
AI Orchestration Intelligence
Practical guides, technical deep-dives, and strategic frameworks from Mirketa's AI architecture team.
How MCP eliminates the M × N integration problem and creates a universal interface between AI models and enterprise systems.
A practical framework for selecting the right multi-agent architecture pattern based on your workflow complexity and performance requirements.
How enterprise leaders can deploy AI agents with confidence using Approval Gates, Ambiguity Resolution, and Trust Calibration.
Your AI Pilot Deserves to Become
Production-Scale Intelligence.
You don't need to replace your core systems to participate in the AI revolution. You need a robust orchestration and data access layer that unifies what you already have.