C
CatalystCore
Loading Page Content...
Advisory & Implementation Consultancy
Advisory & Service Offerings
Strategic advisory and implementation services bridging raw data infrastructure, sovereign private cloud perimeters, and governed autonomous agentic execution.
Sovereign Cloud Perimeter100% Guardrail Enforced
What You Get
Three Fixed-Scope Sprints. Clear Deliverables. Live Results.
Each engagement runs 2–4 weeks with defined outputs — a data readiness blueprint, an AI policy framework, or a live agentic prototype. No open-ended retainers. No vague roadmaps.
PRIORITY-012–3 Weeks
Data & Platform Readiness Assessment
Audit & Blueprint Your Single Source of Truth (SSOT) Data Foundation
Targeted 2–3 week assessment evaluating data quality, schema hygiene, SSOT lakehouse posture (Fabric / BigQuery / Snowflake), vector readiness, and cloud migration TCO.
Fixed Deliverables:
Data Health & Metadata Hygiene Audit
SSOT Target Lakehouse Architecture Blueprint
Vector & RAG Context Readiness Scorecard
Cloud Platform TCO & Migration Roadmap
Target Outcome:Eliminates dirty data and data fragmentation before deploying enterprise AI models.
Book Data Readiness Sprint High Priority Flagship
PRIORITY-022–3 Weeks
AI Assurance & Policy Readiness Assessment
Establish Risk Boundaries, Compliance Guardrails & HITL Triggers
Comprehensive 2–3 week audit evaluating enterprise AI risk posture, RBAC/ABAC data access rules, human-in-the-loop (HITL) approval triggers, FinOps token routing, and safety compliance.
Fixed Deliverables:
AI Risk, Privacy & Compliance Boundary Report
Human-in-the-Loop (HITL) Trigger & Override Matrix
Token FinOps & Model Routing Cost Strategy
Agentic Safety & Data Leakage Audit Framework
Target Outcome:Guarantees 100% operational governance and safety compliance for high-risk enterprise workflows.
Book AI Assurance SprintPRIORITY-032–4 Weeks
Agentic AI PoC Sprint
Deploy a Working Multi-Agent Prototype in 2–4 Weeks
Rapid engineering sprint building and deploying a functional, governed multi-agent AI proof-of-concept on your sovereign cloud environment with real tool execution.
Fixed Deliverables:
Functional Multi-Agent AI Prototype (LangGraph / AutoGen / Azure AI)
Custom Tool Calling & MCP Server Connectors
Sovereign Cloud Landing Zone Deployment
Interactive Executive Demo & Production Roadmap
Target Outcome:De-risks AI adoption upfront by proving ROI with a live, governed prototype in weeks.
Book Agentic AI PoC SprintStructured Framework
Our Core Practice Pillars
Select a pillar to explore strategic advisory capabilities, implementation deliverables, and architecture blueprints
Service 1
Advisory & StrategyStrategy, Risk & AI Readiness Advisory
Strategic advisory evaluating data maturity, API connectivity, security posture, agent safety, and high-impact AI use cases (2–4 week fixed-scope engagement).
AI & Data Readiness Assessment (2–4 Wk Fixed-Scope)
Azure & GCP Enterprise Governance Alignment
Data Risk, Access & Privacy Governance (RBAC/ABAC)
Agentic Safety, HITL Triggers & Permission Tiers
Readiness AuditAzure AI GovernanceGoogle Vertex AI SafetyUse-Case Roadmap
Service 2
Data EngineeringModern Data Foundations & Knowledge Architecture
Consolidate disparate transactional, document, and third-party data into Microsoft Fabric, BigQuery, Snowflake, and SSOT lakehouses with semantic knowledge graphs.
Microsoft Fabric & Google BigQuery Lakehouse Architectures
Single Source of Truth (SSOT) Unified Data Foundations
Semantic Layer & Knowledge Graph Ontologies
AI-Optimized Data Schemas & Chunking Strategies
Microsoft FabricGoogle BigQuerySnowflakeDatabricks
Service 3
Infrastructure & ConnectivityCloud & Solution Architecture Consulting
Architect sovereign, air-gapped landing zones (Azure Secret, Google Cloud Sovereign, AWS GovCloud, On-Prem), low-latency MCP event backbones, private inference hosting, and zero-trust security.
Azure Secret, Google Sovereign & AWS GovCloud Landing Zones
Azure AI Foundry & Google Cloud Vertex AI Infrastructure
Enterprise Integration & Event Backbones (Azure Event Grid, Kafka, Pub/Sub)
Model Context Protocol (MCP) Integration Mesh
Azure Secret / GovCloudGoogle Cloud SovereignAWS GovCloudOn-Premises K8s
Service 4
ImplementationAI Engineering & Agentic Systems Implementation
Build goal-driven autonomous multi-agent workflows across Azure Agentic AI Foundry, Google Agentic AI (Vertex), LangGraph, custom tool calling, and benchmark suites.
Azure Agentic AI Foundry & Google Agentic AI Implementation
Agentic AI Workflow Development (LangGraph, AutoGen, CrewAI)
Custom Tool-Calling & MCP Server Connections
Production RAG & Enterprise Knowledge Systems
Rapid PoCAI PrototypeFeasibility ValidationInteractive Demos
Service 5
OperationsBusiness Process Automation & Transformation
Redesign legacy business processes around hybrid human-agent operating models, web/API automation, AI FinOps token cost control, and digital eForms modernization.
Process Re-Engineering & Human-Agent Workflows
Headless Scraping, Web & System Automation
API Orchestrations & Event-Driven Triggers
AI FinOps & Token Cost Budgeting Management
Process Re-EngineeringHuman-Agent WorkflowsHITL GatesOps Transformation
Complete 12-Point Enterprise Service Matrix
From Readiness Sprints to Governed Execution
Explore our comprehensive 12-item advisory and engineering matrix designed to de-risk transformation, build single-source-of-truth data foundations, and deploy governed agentic AI.
Solution Journey & Info Architecture
How the 12 Offerings Connect Across 4 Lifecycle Stages
Organizations navigate enterprise transformation through four disciplined phases. Each item in our 12-point matrix targets specific operational barriers:
PHASE 1: LAND
Advisory Audit
M-01, 02, 04, 05, 07, 08
PHASE 2: BUILD
SSOT & PoC
M-03, M-09, M-10
PHASE 3: DEPLOY
Governance
M-06, M-11
PHASE 4: SCALE
AI Retainer
M-12 (Claude Partner)
Visual Architecture & Governance Blueprint
Filter:
01Advisory
2–3 WeeksAI Readiness & Strategy Assessment
Comprehensive audit evaluating enterprise AI maturity, data accessibility, security readiness, high-impact use cases, and executive ROI modeling.
Key Deliverables:
- Executive AI Roadmap & Prioritized Use-Case Matrix
- Data & Infrastructure Prerequisites Gap Analysis
- Token & Infrastructure FinOps Cost Model
AI Maturity AuditUse-Case RoadmapROI ProjectionFinOps Modeling
02Advisory
2–3 WeeksData Readiness & Quality Assessment
Targeted assessment evaluating data hygiene, schema consistency, Single Source of Truth (SSOT) posture, and LLM context suitability across systems.
Key Deliverables:
- Data Health & Hygiene Audit Report
- Schema Consistency & Metadata Completeness Scorecard
- SSOT Data Architecture Target Blueprint
Data Quality AuditSSOT ScoringSchema HygieneVector Readiness
03Build
4–8 WeeksData Platform & SSOT Implementation
Engineering operational single-source-of-truth (SSOT) data pipelines across Microsoft Fabric, Google BigQuery, Snowflake, and Databricks.
Key Deliverables:
- Operational Cloud Lakehouse (Fabric / BigQuery / Snowflake)
- Automated ELT/ETL Data Ingestion Pipelines (dbt / Dataform)
- Unified Semantic Layer & Business Data Modeling
Microsoft FabricGoogle BigQuerySnowflakedbtDelta Lake
04Advisory
2–4 WeeksData Platform Modernization & Uplift Assessment
In-depth audit of legacy data warehouses, databases, and reporting infrastructure to identify cost bottlenecks, latency, and modernization pathways.
Key Deliverables:
- Legacy Data Debt & Performance Bottleneck Audit
- Cloud Lakehouse Migration Strategy & TCO Comparison
- Modern Data Architecture Blueprint (Fabric / GCP / AWS)
Cloud ModernizationTCO AuditWarehouse MigrationArchitecture Blueprint
05Advisory
2–3 WeeksData Integration Assessment & Roadmap
Mapping enterprise API topologies, ERP/CRM database connectors, event streaming queues, and multi-cloud data mesh integration milestones.
Key Deliverables:
- Enterprise Data Flow & API Connection Inventory
- Real-Time Streaming & Event-Driven Architecture Spec
- Unified Data Mesh Integration Strategy
API TopologyData MeshEvent StreamingIntegration Roadmap
06Deploy
4–6 WeeksProduction AI Deployment & Operations
Deploying enterprise AI models into production environments with secure API endpoints, FinOps prompt caching, latency optimization, and 24/7 telemetry.
Key Deliverables:
- Hardened Production Model Serving Layer (Azure AI / Vertex / Private vLLM)
- Prompt Caching & Token FinOps Cost Optimization Layer
- CI/CD Pipeline for Model Evaluation & Prompt Tuning
Production DeploymentvLLMPrompt CachingToken FinOpsModel Serving
07Advisory
2–3 WeeksAgentic AI & Multi-Agent Assessment
Evaluating business processes to identify candidate workflows suitable for autonomous agent orchestration, tool integration, and Human-in-the-Loop gates.
Key Deliverables:
- Agentic Workflow Feasibility & Process Mapping Audit
- Human-in-the-Loop (HITL) Gate & Action Budget Design
- Tool Calling & Model Context Protocol (MCP) Connector Spec
Multi-Agent AuditLangGraph SpecHITL Gate DesignMCP Tooling
08Advisory
2–3 WeeksData Sharing & Governance Assessment
Assessing cross-departmental, partner, and B2B data sharing policies, regulatory compliance (CDR, Privacy Act), clean room requirements, and access controls.
Key Deliverables:
- Data Sharing Policy & Privacy Compliance Gap Analysis
- Role-Based / Attribute-Based Access Control (RBAC/ABAC) Spec
- Data Clean Room Architecture & Encryption Requirements
Privacy ComplianceCDR RegulationRBAC / ABACClean Room Spec
09Build
4–6 WeeksData Sharing & Clean Room Implementation
Implementing secure data exchange networks, Data Clean Rooms (Snowflake / BigQuery Clean Rooms), cryptographic access controls, and automated compliance logs.
Key Deliverables:
- Operational Enterprise Data Clean Room Infrastructure
- Fine-Grained Dynamic Masking & Row/Column Level Access Control
- Automated Audit Logging & Compliance Event Streams
Data Clean RoomsDynamic MaskingCryptographic AuditB2B Data Exchange
10Build
3–5 WeeksAgentic AI Implementation (Proof of Concept / Demo)
Rapid engineering of functional multi-agent PoCs and demos leveraging LangGraph, AutoGen, Azure AI Foundry, or Vertex AI Agent Builder with custom tool calling.
Key Deliverables:
- Functional Multi-Agent Interactive Prototype / Demo
- Custom Model Context Protocol (MCP) Server Connectors
- Human-in-the-Loop (HITL) Action Approval Interceptors
LangGraphAzure Agentic AIGoogle Vertex AgentsMCP ServersPoC Sprint
11Governance
3–6 WeeksAI Governance & Runtime Security Framework
Engineering runtime guardrail layers, execution authority limits, prompt injection shields, cryptographic audit trails, and automated compliance enforcement.
Key Deliverables:
- AI Runtime Governance & Guardrail Control Engine
- Action Budget Limits & Transaction Approval Gateways
- Prompt Injection & Jailbreak Defense Pipeline
Runtime GovernanceGuardrails EngineJailbreak DefenseCryptographic Logs
12Scale
Ongoing RetainerStrategic AI Partnering & Advisory Retainer
Dedicated executive AI advisory, Anthropic Claude / Multi-LLM ecosystem co-piloting, model fine-tuning, knowledge graph updates, and FinOps retainer.
Key Deliverables:
- 24/7 Model Drift & Agent Reliability Auditing
- Anthropic Claude & Multi-LLM API Architecture Upgrades
- Continuous Schema Maintenance & Knowledge Graph Tuning
Claude EcosystemMulti-LLM Strategy24/7 AuditingFinOps Retainer
Combine Sprints for Custom Enterprise Engagements
All 12 items can be deployed as standalone fixed-deliverable sprints or combined into multi-stage enterprise modernization programs tailored to your compliance framework.
Engagement Lifecycle
How We Engage: Land, Build, Deploy, Scale
Structured engagement model designed to minimize risk upfront with fixed-scope advisory assessment sprints.
Recommended Entry Tier
Tier 1 • Land2–3 Weeks
AI, Data & Rapid Proof of Concept (PoC) Assessment
Fixed-Scope Advisory & PoC Sprint
Evaluate data maturity, API connectivity, and execute a rapid Proof of Concept (PoC) to validate high-impact AI use cases with zero long-term commitment.
Key Deliverables
Rapid Proof of Concept (PoC)
Executive AI & Data Roadmap
Target Architecture Blueprint
Token FinOps & Risk Audit
Book PoC & Assessment Sprint
50% upon signing / 50% upon final executive roadmap & PoC delivery
Tier 2 • Build4–8 Weeks
Foundation & AI Prototype Engineering
Milestone-Based Core Engineering
Engineer operational SSOT data pipelines, secure cloud landing zones, low-latency API meshes, and functional interactive AI Prototypes.
Key Deliverables
Interactive AI Prototype & Multi-Agent Workflows
Operational SSOT Data Pipeline (Fabric / BigQuery)
Secure Sovereign Landing Zone (Azure Secret / AWS GovCloud / Private vLLM)
API Mesh & Unified Semantic Layer
Inquire About Prototype Sprint
30% Kickoff / 40% Data SSOT Live / 30% Prototype Validation
Tier 3 • Deploy4–6 Weeks
Production AI Deployment & Governed Pilot
Fixed Base + Value Performance Incentive
Transition validated prototypes into full enterprise Production Deployment with HITL approval gates, guardrails, and automated evaluation suites.
Key Deliverables
Enterprise Production Deployment (LangGraph / AutoGen / Azure AI Foundry)
HITL Approval Gates & Action Budget Controls
Custom Tool Calling & MCP Server Connectors
Automated Benchmark & Hallucination Evaluation Suite
Launch Production Deployment
40% Kickoff / 40% Staging Deploy / 20% Production Acceptance
Tier 4 • ScaleOngoing
Managed AI Ops & Enterprise Expansion
Tiered Monthly Retainer
Ongoing production model auditing, cloud and token cost optimization, schema updates, guardrail tuning, and strategic scaling advisory.
Key Deliverables
24/7 Production Agent Drift & Model Auditing
Cloud & Token Cost FinOps Optimization
Schema Updates & Knowledge Graph Maintenance
Guardrail Tuning & Strategic Advisory
Explore Retainer Options
Billed monthly in advance (6 or 12-month contract)
Need a Custom Architecture or Strategy Sprint?
Book our 2–3 week Advisory Assessment Sprint to evaluate data pipelines, cloud security, and high-impact AI agent use cases.
Book Advisory Assessment Sprint