Forward Deployed Engineering with Claude
Claude in your engineering teams and your front office, connected to your systems and governed from day one.
The situation
Most firms have Claude licences. Far fewer have Claude connected to the systems where their work lives, or a delivery method that turns AI-generated code into production software. Dropping an AI assistant into an old process mostly produces faster autocomplete.
session / claude-code / mcp
- read CLAUDE.md done
- mcp sharepoint.search done
- mcp salesforce.query done
- mcp graph.calendar done
- draft brief.md awaiting review
What we deliver
AI-driven development, greenfield and brownfield, run under the Intelligence Studio method in your repository
Briefing, drafting and research workflows for relationship managers, analysts and operations teams
Azure-hosted MCP servers over enterprise data, documents and signals, connecting Microsoft 365, SharePoint, Salesforce, Git and internal APIs
Purpose-built agents and sub-agents for multi-step business processes, with a human in the loop
Use-case-level evaluation across Claude, Azure OpenAI and Amazon Bedrock, selected on cost, speed and data residency
Rollout, guardrails, change management and certification of your engineers
Why now
Salesforce and Claude now run as one estate.
On 26 August 2026, Salesforce and Anthropic announced Claudeforce: Claude as a reasoning model inside Agentforce, and Salesforce available inside Claude. For firms on Salesforce, the question is no longer whether to use AI. It is how to put agents into production safely, with the right permissions, clean data and a human approval step before anything changes a record.
We have been building for this architecture since 2025: a delivery method for AI-driven engineering, MCP connections between Salesforce and Claude, and a human gate between an AI suggestion and a system of record.
- Salesforce FSC
- Agentforce
- Data Cloud
- Microsoft Graph
- SharePoint
- Azure
- Git
- Claude Code
How your data is handled
- Your data stays in your tenant. No client data trains any model.
- Zero Data Retention is configured at the account level.
- Keys are held server-side in a vault. No engineer holds a key.
- Agents run with least privilege: read-only by default, with write access granted per action.
- Every AI action can be reconstructed: prompt, model, output, cost, and the person who signed it.
Proof
- Equipment finance platform. A lending platform engineered from the data layer up, with agentic services across several models exposed through MCP servers, and human-in-the-loop throughout.
- Post-trade settlement (discovery). Three weeks from first conversation to a reconstructed trade journey, six named and costed failure modes, and a reference architecture reviewed by the client's CTO.
Scorpiosys is a member of the Claude Partner Network.