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AI Data Readiness Assessment
A 3-week diagnostic that maps your existing data landscape, scores data quality across critical domains, identifies AI use case data dependencies, and produces a prioritized data modernization roadmap.
AI Data Foundation Services
AI Data Foundations: Build the Data Layer Your AI Actually Needs
84% of business leaders say data quality is the #1 blocker to AI success. Mirketa's AI data foundation services unify, govern, and prepare your enterprise data across Salesforce Data Cloud, Snowflake, and your existing systems so your AI agents, models, and analytics can finally deliver trusted, production-grade results.
Salesforce Data Cloud Certified
Snowflake Partner
HIPAA & GDPR Ready
AI-Ready Data Architecture
84%
of business leaders say data quality is the #1 blocker to AI success
Generative AI, agentic AI, and traditional machine learning all share one dependency: trustworthy, accessible, and well-governed data. Without an AI-ready data foundation, even the most sophisticated AI tools produce hallucinated answers and decisions executives can't defend.
- Salesforce Data Cloud implementation & grounding
- RAG architecture for enterprise AI agents
- Zero Copy integration with Snowflake & Databricks
- Data governance built for AI compliance
- Master data management for AI personalization
The Data Foundation Problem
Why AI Without a Data Foundation Always Fails
Generative AI, agentic AI, and traditional machine learning all share one dependency: trustworthy, accessible, and well-governed data. Without an AI-ready data foundation, even the most sophisticated AI tools produce hallucinated answers, biased recommendations, and decisions executives can't defend.
Most enterprise data was never designed for AI. It lives in silos across CRM, ERP, marketing automation, support systems, data warehouses, and spreadsheets. It's inconsistent in format, governed differently by each team, and rarely captured with the metadata AI systems need to retrieve and reason about it.
Mirketa's AI data foundation services address this gap directly. We design, build, and govern the unified data layer that turns your fragmented enterprise data into a strategic asset for AI using proven architectures including Salesforce Data Cloud, Snowflake, Zero Copy integration, vector databases, and Retrieval-Augmented Generation (RAG).
Our Services
What Mirketa's AI Data Foundation Services Include
Our enterprise data architecture consulting covers the full lifecycle of building AI-ready data from initial assessment through unified architecture design, integration, governance, and ongoing optimization.
02
Salesforce Data Cloud Implementation
End-to-end Salesforce Data Cloud consulting and implementation including data ingestion, identity resolution, calculated insights, segmentation, activation, and Agentforce data grounding. Includes Zero Copy integration with Snowflake, Databricks, BigQuery, and Redshift.
03
Enterprise Data Integration
Salesforce Integration Services and enterprise iPaaS implementation using Boomi, MuleSoft, and native API frameworks connecting CRM, ERP, data warehouses, and SaaS systems into a single AI-ready data fabric.
04
RAG Implementation Services
Design and deployment of Retrieval-Augmented Generation systems that ground large language models in your enterprise data. Includes embedding strategy, vector database setup, chunking architecture, hybrid search, and evaluation frameworks.
05
Data Governance for AI
Implementation of data governance frameworks tailored for AI workloads covering data lineage, access controls, PII handling, consent management, model-data versioning, and audit trails for AI decision explainability.
06
Master Data Management (MDM)
Unified customer, product, and account master data the foundation that makes AI personalization, agent grounding, and predictive analytics actually trustworthy at enterprise scale.
Reference Architecture
Mirketa's AI-Ready Enterprise Data Architecture
Every Mirketa data foundation engagement is built on a layered reference architecture proven across nonprofits, healthcare, manufacturing, and hi-tech deployments supporting both traditional analytics and modern agentic AI workloads from the same data layer.
1
Source Systems
Your existing systems of record Salesforce CRM, NetSuite ERP, Oracle Fusion, ServiceNow, Workday, marketing automation, and data lakes connected via Salesforce Integration Services, Boomi, MuleSoft, or native APIs.
2
Unified Data Fabric
Salesforce Data Cloud as the customer data hub, integrated with Snowflake / Databricks / BigQuery as the analytical foundation. Zero Copy architecture eliminates duplicate data movement and ensures every AI workload runs on the same trusted dataset.
3
AI Data Services
Vector databases (Pinecone, Weaviate, pgvector), embedding generation pipelines, RAG retrievers, semantic search indexes, and feature stores that prepare data for both generative and predictive AI consumption.
4
Governance & Observability
Data lineage, quality monitoring, access controls, PII detection, consent management, and audit trails all integrated with your AI Roadmap & Governance framework for end-to-end compliance.
5
AI Consumption Layer
AI agents (Agentforce, custom LLM agents), predictive analytics, Einstein AI, dashboards, and applications all consuming from the same governed data layer for consistent, trustworthy results.
Technology Partners
Salesforce Data Cloud, Snowflake, and the AI Data Stack We Build On
Mirketa is platform-pragmatic. We recommend the right architecture for your stack, budget, and use case not a single-vendor lock-in.
Customer Data Platform
Salesforce Data Cloud
Our primary recommendation for customer data unification, Agentforce grounding, and CRM-integrated AI. Native integration with Salesforce CRM eliminates overhead.
Analytical Foundation
Snowflake, Databricks, BigQuery, Redshift
For analytical data foundations and Zero Copy integration with Data Cloud. Supports both structured analytics and AI workloads from the same platform.
Vector Databases
Pinecone, Weaviate, Qdrant, pgvector
For RAG and semantic search workloads including Salesforce native vector storage for Agentforce-grounded AI agents.
Integration Platforms
Boomi, MuleSoft, Workato
Enterprise iPaaS and native Salesforce Integration Services for connecting source systems into a unified AI-ready data fabric.
AI Platforms
OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Agentforce
We build data foundations that work with any AI platform grounding your chosen LLM in your enterprise data for trusted, production-grade results.
Governance Tools
Collibra, Alation, Salesforce Privacy Center
Data governance, lineage, and audit-ready documentation built into every engagement, not bolted on as a separate phase.
Our Approach
How We Build Your AI Data Foundation 4-Phase Methodology
Phase 1
Assess
Map current-state data architecture, score data quality, identify AI use case data requirements, and document gaps across all critical data domains.
Output: AI data readiness scorecard and prioritized backlog
Phase 2
Design
Architect the target-state data foundation. Select platforms, define integration patterns, design data models, and plan governance controls for AI workloads.
Output: Reference architecture, technology selection, implementation roadmap
Phase 3
Build
Execute data integration, Salesforce Data Cloud implementation, vector database deployment, RAG pipeline setup, and governance configuration in production.
Output: Production AI data foundation
Phase 4
Operate
Ongoing managed services — data quality monitoring, governance reviews, schema evolution, AI model-data alignment, and performance optimization.
Output: Continuously improving, audit-ready AI data foundation
Client Results
AI Data Foundation Use Cases Our Clients Have Built
Healthcare Data Foundation for AI Care Coordination
HIPAA-compliant data foundation integrating EHR, Salesforce Health Cloud, claims data, and patient engagement systems supporting AI-powered care coordination, risk stratification, and patient outreach via Mirketa's Elixir platform.
✓ HIPAA CompliantRAG-Powered Customer Service for SaaS
RAG implementation grounding Agentforce service agents in real-time product documentation, support tickets, and knowledge base content reducing first-contact resolution time by 45% and deflecting 60% of Tier-1 cases.
↓ 45% Resolution TimeCRM-ERP Data Unification for Manufacturing
Salesforce Integration Services connecting Sales Cloud, Manufacturing Cloud, Oracle ERP, and Snowflake into a single data foundation that powers AI-driven sales forecasting and supply chain optimization.
✓ Zero Copy ArchitectureSalesforce Data Cloud for Nonprofits
Unified donor, program, and impact data foundation feeding personalized fundraising AI, donor lifetime value prediction, and impact reporting built on Salesforce Nonprofit Cloud and Data Cloud.
✓ Donor AI Enabled
Why Mirketa
Why Enterprises Trust Mirketa for AI Data Foundation Services
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Cross-platform expertise. Certified specialists in Salesforce Data Cloud, Snowflake, Databricks, and vector databases we build hybrid architectures that fit your real stack, not idealized vendor demos.
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AI-first data architecture. Every foundation we design is built for both today's analytics and tomorrow's AI agents eliminating expensive re-architecture later.
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Salesforce Integration Services depth. 15 years of Salesforce CRM consulting and Salesforce Implementation Services means we know how to integrate Data Cloud with the rest of your enterprise without breaking what already works.
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Governance built in, not bolted on. Data governance, lineage, and audit-ready documentation are part of every engagement not a separate phase.
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Industry data models. Pre-built nonprofit, healthcare, manufacturing, and hi-tech data models cut implementation time by 30–50%.
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Managed services continuity. Mirketa stays with you after go-live with ongoing data quality, integration, and AI data lifecycle management.
Proven Results Across Industries
0
Years Salesforce & Data Experience
0
% Faster with Pre-built Data Models
0
% Reduction in Resolution Time (RAG)
0
% Tier-1 Case Deflection Rate
FAQ
Frequently Asked Questions About AI Data Foundation Services
No. Salesforce Data Cloud is our most-recommended customer data layer for organizations already running Salesforce CRM, because it eliminates integration overhead and natively grounds Agentforce. But we build AI data foundations on Snowflake, Databricks, BigQuery, and hybrid architectures as well the right answer depends on your existing stack, AI use cases, and governance requirements.
A traditional data warehouse is optimized for structured analytical queries reports, dashboards, BI. An AI data foundation extends that to support unstructured data (documents, conversations, images), vector embeddings, real-time retrieval for RAG applications, and continuous data flows for agentic AI. It also adds AI-specific governance like model-data lineage and explainability.
A focused Salesforce Data Cloud implementation connecting 3–5 source systems with identity resolution and basic segmentation typically takes 8–12 weeks. Enterprise Data Cloud rollouts with Agentforce grounding, advanced calculated insights, and Zero Copy integration with Snowflake run 16–24 weeks. Mirketa's pre-built accelerators reduce these timelines by 30–40%.
Retrieval-Augmented Generation (RAG) is the architecture pattern that grounds large language models in your enterprise data, eliminating hallucinations and making AI answers traceable to source documents. If you're deploying AI agents (Agentforce, custom chatbots, internal copilots) that need to answer questions using your company's specific knowledge, you need RAG or you'll deploy an AI that confidently invents wrong answers.
Every AI data foundation we build includes governance controls mapped to your industry HIPAA for healthcare, SOC 2 and GDPR for SaaS, PCI-DSS for financial services. We implement PII detection and masking, consent management, fine-grained access controls, audit logging, and AI decision explainability from day one. See our AI Roadmap & Governance services for the full governance framework.
Yes. Data warehouse modernization to AI-ready architectures is one of our most common engagements. We've migrated organizations from legacy warehouses (Oracle, Teradata, on-prem SQL Server) to modern AI-ready stacks built on Snowflake, Databricks, and Salesforce Data Cloud with minimal disruption to existing analytics consumers.
Free Assessment
Ready to Build an AI-Ready Data Foundation?
Book a free 30-minute AI data readiness call with one of Mirketa's senior data architects. We'll map your current data landscape, identify the gaps blocking your AI initiatives, and give you a clear next step whether that's Salesforce Data Cloud, a Snowflake-based architecture, or a hybrid approach.
- No commitment required just a clear-eyed assessment
- Senior data architect not a sales rep
- Platform-agnostic recommendation for your stack
- Response within 1 business day
Get Your Free AI Data Readiness Assessment
Tell us about your data landscape and AI goals we'll respond within 1 business day.