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Six flagship offerings. One production delivery standard.

AI workflow automation, copilots, analytics modernization, FinOps, AI security, and digital identity are the entry points. Underneath sits the delivery depth regulated enterprises actually need: architecture, data, cloud, governance, security, integration, runbooks, and handover.

See How We Engage
Flagship engagements

Start from the trigger, not the capability list.

When

Manual, document-heavy, approval-heavy work is scaling with headcount.

AI Workflow Automation

Ships: Governed AI workflow with ingestion, extraction, human review, exception handling, and audit trails.

Workflow map · controls · runbook · measured throughput
Scope workflow automation →
When

Teams need trusted answers from internal knowledge, not another chatbot.

Enterprise AI Copilots

Ships: Grounded copilot with permissions, citations, an evaluation harness, an adoption loop, and an operating model.

Evaluation harness · source map · access model · usage dashboard
Scope a copilot →
When

Dashboards are not trusted and metrics differ across teams.

BI & Analytics Modernization

Ships: Semantic layer, governed metrics, reconciled dashboards, and data quality checks.

Metric catalog · lineage · executive dashboard · ownership model
Rebuild analytics trust →
When

Cloud spend is rising faster than business value.

Cloud FinOps

Ships: Architecture-level cost remediation and a FinOps operating model, with the savings target in the SOW.

Savings tracker · workload plan · showback / chargeback model
Control cloud cost →
When

An AI system is approaching launch, audit, or board review.

AI Security Review

Ships: Threat model, red-team findings, framework mapping, and a prioritized remediation backlog.

Board-ready risk memo · technical findings · remediation backlog
Review AI risk →
When

Credentials, identity, verification, or KYC must operate at institutional scale.

Digital Credentialing & Identity

Ships: Open-standard credentialing or sovereign identity infrastructure on W3C, OpenID4VC, and MOSIP.

Standards map · credential lifecycle · verification flow · revocation model
Map the trust system →
Buyer router

Not sure where it fits? Start from the problem.

Most enterprise problems do not map cleanly to one offering. Bring the problem; we map the engagement across the pillars it actually touches.

A backlog of documents or cases is growing with headcountAI Workflow Automation →People cannot find or trust answers in your own knowledgeEnterprise AI Copilots →Leaders argue over which number is correctBI & Analytics Modernization →The cloud bill is climbing faster than the businessCloud FinOps →An AI system has to clear security, audit, or a boardAI Security Review →Identity, credentials, or verification must hold at scaleDigital Credentialing & Identity →
Under the flagships

Four delivery pillars under the flagships.

AI

Applied AI in production.

AI Use Case Discovery & PrioritizationAI Governance & Policy FrameworkAI Workflow AutomationEnterprise AI CopilotsMulti-Agent SystemsDomain LLM Fine-Tuning & RAGFraud & Anomaly Detection (BFSI)Clinical & Operational AI (Healthcare)

Data

Governed, versioned, regulator-ready data layer.

Data Governance ProgramRegulatory Data ComplianceData Foundation / Lakehouse BuildReal-Time Pipeline EngineeringData Product EngineeringBI & Analytics ModernizationPredictive Analytics & ML Modeling

Cloud

Architecture, migration, operations across AWS, Azure, GCP.

Cloud Readiness Assessment & RoadmapEnterprise Cloud MigrationLegacy System ModernizationAI-Ready Cloud InfrastructureDevOps & Platform EngineeringCloud Cost Optimization / FinOpsManaged Cloud Operations

Cybersecurity & Digital Trust

Security and digital trust for regulated systems.

Security Posture Assessment & RoadmapVAPT & Application Security TestingAI System Security ReviewLLM Red-TeamingEveryCRED Digital CredentialingMOSIP Sovereign Identity
FAQ

Questions buyers ask about the offerings

Anything else, email the practice.

Most enterprise problems do not map cleanly to one offering. A claims backlog is part workflow automation, part data, part integration. Bring the problem to a scoping conversation and we map the engagement across the pillars it actually touches.

No. The six flagships are common entry points. Underneath sits delivery depth across AI, data, cloud, cybersecurity, and digital trust.

Discovery and assessment work typically starts in the $40K to $60K range. Production builds typically start from $200K. OPERATE retainers start from $12K–$15K per month depending on discipline and scope. Exact scope and pricing are written into the SOW after a scoping conversation.

No. We are cloud-agnostic across AWS, Azure, and Google Cloud, and we make the architectural decisions that determine exit cost explicitly with you on day one.

Beyond the flagships

Most engagements draw from multiple capabilities across pillars.

Tell us what you are scoping, and we will map our depth to your needs.