Conviction Engine
Relationship managers run on memory and scattered notes.
Four-signal conviction scoring across deal types, with a coaching agent that surfaces the right investor before the partner meeting.
Explore Conviction EngineAI Forward Deployed Engineering, powered by Intelligence Studio.
Architect-led engineers who work in your repository and ship production AI for regulated industries.
PerspectiveOctober 2026
The SDLC was built for humans. AI changes the equation.
- Anthropic (Claude)Member of the Claude Partner Network
- SalesforceSalesforce Consulting Partner
- MicrosoftMicrosoft Solutions Partner
Intelligence Studio
Decisions before code. A human signature at every gate.
Industry Intelligence
What we have built
Industry Intelligence is built and delivered under Intelligence Studio, configured to your estate rather than rebuilt for it.
Cognition Studio
Cognition Studio: AI-guided learning and assessment for education. Coming soon.
Request early accessBrahma
Multi-step care journeys are coordinated by hand, and patient drop-off is found late.
A governed ten-step patient journey with HIPAA-grade controls. MVP live in four weeks.
Explore BrahmaPlatforms
Where we build
Forward Deployed Engineering with Claude
- Claude Code and the Agent SDK inside your delivery lifecycle
- Cowork rolled out to front-office teams with guardrails
- MCP servers over enterprise data, documents and signals
Forward Deployed Engineering for Salesforce
- Agentforce agents grounded in your own data
- Financial Services Cloud and Health Cloud modernization
- Salesforce connected to Claude through MCP, with every action written back to the record
Forward Deployed Engineering on Microsoft
- Microsoft Graph API, Teams and meeting transcripts
- SharePoint and Outlook
- Azure AI Search and Azure-hosted MCP servers
Customer Stories
Production AI, delivered under scrutiny
Global capital advisory firm
Three production AI capabilities released 30 June 2026. Four engineers over 16 weeks, against a plan of eight engineers over 48. Every score traceable to its inputs.
Private equity GP
Conviction scoring across four signals and multiple deal types, with a coaching agent that surfaces the right investor before the meeting.
Equipment finance platform
A lending platform engineered from the data layer up. Agentic services run across Claude and other models through MCP servers, each model selected per task on cost, speed and data residency. DevSecOps pipelines are built to GDPR, PCI DSS and SOC 2 control expectations.
Why Scorpiosys
Not a seat filled. An outcome owned.
| Staff augmentation | Product-led FDE | Scorpiosys FDE | |
|---|---|---|---|
| Accountable for | Hours and tickets | Adoption of one vendor's product | An outcome running in production |
| Who designs | You write the spec | The product shapes the design | Architecture signed with your architects before any code |
| Scope | One team, one backlog | One product | Across Salesforce, Claude and Microsoft |
| How AI is used | An assistant added to the existing process | A feature of the product | An AI development lifecycle: scored sprints, human gates |
| Arrives with | A CV | Product knowledge | Build · Learn · Deliver certification: a real system already built and delivered under Intelligence Studio, plus the Intelligence Studio toolkit |
| Left behind | Billed hours | A deployed product | Code, signed artifacts, and your own engineers certified |
| Measured by | Rate per hour | Licences consumed | Cost to reach production |
Staff augmentation
- Accountable for
- Hours and tickets
- Who designs
- You write the spec
- Scope
- One team, one backlog
- How AI is used
- An assistant added to the existing process
- Arrives with
- A CV
- Left behind
- Billed hours
- Measured by
- Rate per hour
Product-led FDE
- Accountable for
- Adoption of one vendor's product
- Who designs
- The product shapes the design
- Scope
- One product
- How AI is used
- A feature of the product
- Arrives with
- Product knowledge
- Left behind
- A deployed product
- Measured by
- Licences consumed
Scorpiosys FDE
- Accountable for
- An outcome running in production
- Who designs
- Architecture signed with your architects before any code
- Scope
- Across Salesforce, Claude and Microsoft
- How AI is used
- An AI development lifecycle: scored sprints, human gates
- Arrives with
- Build · Learn · Deliver certification: a real system already built and delivered under Intelligence Studio, plus the Intelligence Studio toolkit
- Left behind
- Code, signed artifacts, and your own engineers certified
- Measured by
- Cost to reach production
Compare the cost of the outcome, not the hourly rate. Our last Financial Services Cloud programme took 64 engineer-weeks against a plan of 384.
| Planned | Delivered |
|---|---|
| 8 engineers 48 weeks | 4 engineers 16 weeks |
Built for regulated industries
- 01 Data stays in the client's environment.
- 02 Every AI action can be reconstructed for an auditor.
- 03 Agents get least-privilege access.
- 04 A human approves before any system of record changes.
Ways to engage
- Augment
- Our engineers join yours, each Build · Learn · Deliver certified and carrying the Intelligence Studio toolkit. Best when you hold the domain and need AI capability now.
- Enable
- We certify your engineers in the method and the toolchain. Best when you intend to own the capability.
- Deliver
- We build it end to end, and your sponsor signs every gate. Best when the outcome matters more than the mechanics.
Start with your problem.
- AI demo and assessment. What AI can do in your environment.
- Problem structuring. We frame the highest-value opportunity.
- Prototype. You see the solution before any commitment.
- Your decision. Build it with us, or keep the prototype and decide later.