CLEAR PURPOSE. PRACTICAL AI.
We help teams identify the right opportunities, build agents connected to their knowledge and systems, and measure how well they work.
For banking, wealth management & knowledge-heavy operations
THE WORK COMES FIRST
The hard part is connecting AI to how your organization actually works.
Knowledge is scattered. Systems don’t always connect. Exceptions matter. And someone needs to be accountable when an agent gets it wrong.
Scope AI brings business analysis, systems thinking and hands-on engineering together to close that gap—one well-defined workflow at a time.
01 / HOW WE HELP
Start where you are.
Build only what the work needs.
Unsure where AI earns its place? Map the work, exceptions, data and access. Compare buying, configuring and building before committing.
YOU LEAVE WITHPrioritized use cases, a process map, readiness and assumptions register, value hypothesis and scoped pilot proposal.
Turn an agreed opportunity into a bounded, testable pilot. Define behavior, acceptance criteria, integrations, review gates and failure handling.
YOU LEAVE WITHA specification, architecture, working pilot, evaluation results and implementation documentation.
Move beyond the demo. Connect approved knowledge and systems, establish permissions and monitoring, and prepare people to use and support the solution.
YOU LEAVE WITHIntegrations, permission model, deployment configuration, operating runbook and handover materials.
Understand what happens in real work. Review recurring failures, strengthen context, compare changes and manage cost and response time.
YOU LEAVE WITHAn evaluation scorecard, improvement backlog, regression checks and periodic outcome reviews.
02 / OUR APPROACH
Two connected uses of AI.
Human accountability throughout.
AI assists with requirements, design, code, test creation, documentation and review. Clear specifications and human validation keep delivery aligned with the intended outcome.
Agents use approved business knowledge and tools to support or execute workflows. We define where reasoning helps, where deterministic logic belongs and where a person must decide.
↶ Measurement feeds back into the specification. Improvement is part of delivery.
We use specification-driven, AI-assisted engineering with review and validation gates. GitHub Spec Kit supports structured development processes and reusable templates. It structures delivery; it is not the customer’s business runtime. Python workflows, APIs and MCP integrations can connect approved tools where appropriate. A purchased agent, configured platform or custom component may be the right fit—there is no requirement to build a new framework or multi-agent system.
INSIDE A WORKING AGENT
Cooperating components, not a conveyor belt.
Select a part to explore the design decisions.
These are design responsibilities, not guarantees of compliance or security from any single product.
Microsoft FoundryPrimary focus
AWS BedrockSecondary focus
Architecture informed by the wider ecosystem, including Google and NVIDIA. No partnership or certification is implied.
03 / POSSIBILITIES IN PRACTICE
Illustrative workflows.
Clear review points. Measurable objectives.
Keep intent, acceptance criteria and testing connected.
Bring the evidence together before a person decides.
Make the decision easier to examine and explain.
Shervin Sadeghi
Founder, Scope AI
04 / EXPERIENCE THAT CONNECTS
Before we decide what an agent should do, we need to understand what good work looks like.
Shervin Sadeghi brings senior business and business systems analysis experience in banking and wealth management, including roles at RBC, CIBC and TD.
His work spans KYC/AML, investment performance, requirements, data mapping, SQL validation, acceptance criteria, SIT/UAT, production verification and release readiness.
That foundation now connects to hands-on automation and AI: Playwright with JavaScript and Python, AI coding assistance, Perfecto mobile testing, and a Python agent project integrating workflow state, session memory and orchestration with Jira and Confluence through MCP.
Past employers reflect the founder’s experience, not Scope AI client relationships or endorsements.
Credentials provided by the founder; current standing not independently verified.
A FEW PRACTICAL QUESTIONS
LET’S FIND THE RIGHT STARTING POINT
Something repetitive. Something fragmented.
Something your people know could work better.
Our first conversation identifies a candidate process and whether a discovery engagement makes sense.