Agentic AI Strategy & Roadmap
Find and rank the agent opportunities worth funding, with a value case and a delivery plan.
- Use-case discovery and value scoring
- Platform and model choices
- Funding, licensing, and consumption planning
Services
Consulting and engineering for the full agent lifecycle.
Our solution consultants help leadership and delivery teams move from AI ambition to secure, observable agents in production, on Salesforce and across the wider enterprise.
Strategy & Architecture
Enterprise & Solution Architecture
Reference architectures that scale from the first agent to hundreds, across Salesforce and the wider estate.
- Agent, data, integration, and identity blueprints
- Salesforce well-architected reviews
- Scalability, limits, and cost design
A2A & Multi-Agent Architecture
Design agents that collaborate: orchestrators, specialists, and third-party agents working as one system.
- Agent2Agent (A2A) and MCP interoperability
- Orchestrator and specialist routing patterns
- Agent identity, trust boundaries, and registries
Build & Deliver
Agentforce Implementation
End-to-end build of Agentforce agents, from topics and actions to channels and launch.
- Agentforce Builder and Agent Script
- Service, sales, field, and employee agents
- Slack, Teams, web, and voice channels
Data 360 & AI-Ready Data
Unified, governed data that gives agents accurate context.
- Data 360 (formerly Data Cloud) implementation
- Zero-copy access to Snowflake and Databricks
- Retrieval and RAG design with permission awareness
Integration & Custom AI Engineering
Connect agents to every system and model they need, securely.
- MuleSoft, APIs, and event-driven integration
- MCP servers and tools for enterprise systems
- Custom agents on Bedrock, Microsoft Foundry, and Vertex AI
Agentic SDLC
Use AI agents across the delivery lifecycle, and manage agents with the same discipline as code.
- AI-assisted planning, coding, and test generation
- Versioned agents with automated tests and evaluations
- Promotion through environments with Salesforce DX and DevOps Center
Secure & Govern
Salesforce Security & Compliance
A secure platform foundation before agents add new ways to reach your data.
- Permission-set-led access and sharing reviews
- Shield: encryption, event monitoring, field audit trail
- Evidence mapped to SOC 2, HIPAA, GDPR, and internal policy
Agentforce Security
Controls designed for autonomous agents, not just users.
- Einstein Trust Layer configuration and data masking
- Least-privilege agent users and scoped actions
- Prompt-injection defenses and red-team testing
DevSecOps for AI & Salesforce
Security checks that run automatically, every time something changes.
- Static analysis for Apex, LWC, and metadata
- Secret scanning, dependency checks, and policy as code
- Agent and prompt security tests as pipeline gates
AI Governance & Center of Excellence
An operating model that lets you move fast and stay defensible.
- Responsible AI policy and risk tiers
- Approval paths and human-in-the-loop design
- CoE setup, enablement, and adoption playbooks
Run & Improve
Agent Observability & AgentOps
Know what every agent did, why, and whether it worked.
- Session tracing and agent health monitoring
- Evaluations, conversation testing, and quality scoring
- Cost, consumption, and drift tracking with alerts
Managed AI Operations
We run and keep improving your agents after launch.
- Ongoing monitoring with agreed response times
- Release management for new platform capabilities
- Continuous tuning from production feedback
How we engage
From first workshop to agents in production.
Step 01
Discover
Prioritize use cases, assess data and security readiness, and agree how success will be measured.
Step 02
Prove
Build a governed pilot against a measured baseline, with security and evaluation built in.
Step 03
Scale
Industrialize with multi-agent architecture, DevSecOps pipelines, and adoption programs.
Step 04
Run
Observe, optimize, and adopt new platform capabilities as they become generally available.