We build scalable data platforms that connect the reasoning of Salesforce Agentforce and Data Cloud with the infrastructure power of AWS. Safe, compliant, and architected to drive measurable business outcomes.
Enterprise AI fails when it is treated as an isolated pilot. We propose a structured, three-tier framework that ensures your data infrastructure, trust guardrails, and platform engineering are ready for production deployment at enterprise scale.
Focus. Clear definition of business value metrics and identification of high-impact AI opportunities.
Deliverables. Comprehensive data quality and integration gap assessments, data readiness mapping, and the definition of strict AI trust guardrails, operational controls, and compliance frameworks.
Focus. Proving capability and validating business outcomes within real operational workflows using measurable KPIs.
Deliverables. Securely connecting and validating Salesforce and enterprise data, deploying guardrails in production-like environments, and establishing clear user acceptance and operational readiness parameters.
Focus. Industrialising AI platforms and expanding proven AI value across cross-functional global operations.
Deliverables. Standardizing, governing, and optimizing data layers at scale, institutionalizing continuous model governance, and embedding autonomous agent ecosystems natively into daily workflows.
| Dimension | Foundry | Forge | Frontier |
|---|---|---|---|
| Business value clarity | Identify and prioritise high-impact AI opportunities | Validate business outcomes with measurable KPIs | Expand proven AI value across functions |
| Data & integration readiness | Assess data quality, availability, and integration gaps | Connect and validate Salesforce and enterprise data | Standardise, govern, and optimise data at scale |
| Risk, trust & compliance | Define AI guardrails, controls, and trust frameworks | Validate guardrails within real operational workflows | Institutionalise governance, compliance, and oversight |
| Technology confidence | Assess AI feasibility, tooling fit, and architecture | Prove AI performance in production-like environments | Industrialise AI platforms and agent ecosystems |
| Adoption & scalability | Design adoption strategy and future scale roadmap | Validate user acceptance and operational readiness | Embed AI into daily operations and enterprise processes |
End-to-end configuration and deployment of Salesforce Agentforce and custom AI agents built to handle customer journeys autonomously.
Laying the foundation for AI-driven decisions by combining transactional histories, external databases, and real-time data streaming via Data Cloud, Snowflake, and MuleSoft.
A highly structured 3–6 week accelerator program designed to give complete cost visibility, optimize underutilized cloud resources, establish cost guardrails, and deliver 30–40% potential annual savings.
Account managers relied on disconnected spreadsheets and manual data lookups, losing critical cross-sell and upsell speed.
Deployed real-time customer data summarization and conversational sales assistance powered by Agentforce and Data Cloud.
Spend 30 minutes with a data architect. Let's look at your current data stack and outline a concrete path to operational AI readiness.