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AI Discovery Sprint

Custom
3-day deep assessment • scoped per project

A structured 3-day engagement to map your AI opportunity, validate your data readiness, and produce an enterprise-grade architecture document for your vertical.

Vertical AI opportunity mapping
Data readiness assessment
Architecture document (delivered)
Build vs. buy analysis
ROI model and timeline
Technology stack recommendation
Compliance and security review
30-day follow-up call included
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Pricing is negotiated directly with each client based on scope, vertical, data complexity, and deployment environment. Contact us to start the conversation.

FAQ

Enterprise AI Questions

Common questions from financial institutions, healthcare organizations, and enterprise security teams.

We have production-proven systems for six verticals: FinGuard AI (financial fraud, AML, credit risk, LC validation), CyberShield AI (enterprise threat detection, SOC automation), MedAI Diagnostics (lab analysis, medical imaging, multilingual clinical docs), MedInsure AI (claims fraud, underwriting AI), AgenticAI Platform (multi-agent orchestration, custom MCP), and Enterprise AI Delivery (RAG pipelines, LLM fine-tuning, cloud deployment).

The Discovery Sprint takes 3 business days and delivers a full architecture document. Full vertical deployments typically run 8–16 weeks from architecture sign-off to production, depending on data readiness, integration complexity, and compliance requirements. We provide a detailed timeline after the Discovery Sprint.

Yes — regulated industries are our primary focus. Our FinGuard AI is built for AML and financial compliance requirements. MedAI Diagnostics is designed with clinical-grade accuracy and documentation standards. All systems include full audit trails, data isolation, and compliance documentation. We're experienced with HIPAA, GDPR, and financial regulatory environments.

MCP (Model Context Protocol) is an open standard that allows AI agents to securely access enterprise tools, databases, and APIs through structured, auditable interfaces. We design custom MCP servers that give your AI agents controlled access to your internal systems — without exposing raw data and without vendor lock-in. It's the infrastructure layer that makes enterprise agentic AI trustworthy.

Integration is scoped during the Discovery Sprint. We work with REST APIs, message queues (Kafka, RabbitMQ), SQL/NoSQL databases, SIEM platforms (Splunk, Sentinel), EHR systems, and core banking APIs. Custom MCP servers provide the clean interface layer between your data infrastructure and the AI agents — preserving your security posture throughout.

After the 6-month program, your systems are in stable production with full documentation, monitoring, and runbooks. You can continue with a retainer for ongoing optimization and model updates, or maintain the system internally using the documentation we provide. Most clients opt for a quarterly model review retainer to keep pace with evolving threats and domain knowledge.

Let’s Discuss Your Project

Request a demo, tell us about your vertical, and we’ll prepare a scoped proposal tailored to your organisation. No standard price list — every engagement is built around your requirements.

Request a Demo