Engagement models

Pick the model that matches the pressure you are under.

AI practice

Adopt AI without betting the institution on it.

Three ways we help regulated teams turn AI from a promising pilot into a governed advantage — a clear adoption strategy, day-to-day productivity that actually sticks, and AI-accelerated modernization of the systems you cannot afford to get wrong.

Strategy & adoptionA costed, prioritized roadmap and the operating model to run AI under regulatory oversight.
Productivity & enablementCopilots, knowledge assistants, and agents grounded in your data — measured, not just demoed.
Accelerated modernizationUnderstand, test, and migrate legacy platforms in months — with evidence at every step.
LEGACY → MODERN TEST-DRIVEN legacy monolith analyze REGRESSION TEST NET svc svc svc svc INCREMENTAL HUMAN-VALIDATED AUDITABLE
AI · 01 / Strategy & adoption

Help your organization adopt AI — deliberately.

Most AI programs stall in the gap between an exciting pilot and a system you can run, govern, and defend. We give you a costed, prioritized roadmap and the operating model to execute it — grounded in your regulatory reality, not a vendor's slide deck.

When to call us

  • You have promising pilots but no path to production or ROI.
  • The board wants an AI strategy — and a clear risk position.
  • You need to prioritize use cases by value, feasibility, and risk.
  • You're preparing for OSFI E-23, privacy, or procurement scrutiny.

What you get

  • An AI readiness & value assessment with a ranked use-case portfolio.
  • A costed roadmap with ROI models and explicit success metrics.
  • A governed AI operating model: roles, policies, accountability.
  • Responsible-AI & model-risk foundations mapped to your obligations.
Readiness assessmentUse-case portfolioROI modelingOperating modelResponsible AI
Fixed-scope entry point

The AI Readiness Assessment.

The lowest-risk way to start. In two to three weeks we rank your use cases by value, feasibility, and risk, review your data and governance posture against OSFI E-23 and your privacy obligations, and deliver a costed roadmap with an honest go / no-go view — yours to keep, whoever builds it.

Ranked use-case portfolioE-23 & privacy gap viewCosted roadmapGo / no-go recommendation
Book the assessment 2–3 weeks · Fixed scope · Senior-led
AI · 02 / Productivity & enablement

Set up AI that makes your teams measurably faster.

We put copilots, knowledge assistants, and agents into the daily workflow — grounded in your own data, wrapped in guardrails, and measured so the gains are real. The goal is durable productivity, not a novelty everyone abandons after a month.

When to call us

  • Staff are pasting sensitive data into public chatbots.
  • You want an assistant over your own documents and systems.
  • You need to roll out AI coding tools with security and standards.
  • "Agents" keep getting demoed, but nothing reaches production safely.

What you get

  • Governed RAG knowledge assistants over your permissioned data.
  • Agentic workflows with traceability and human checkpoints.
  • Developer-productivity enablement (Copilot, agentic coding) with measurement.
  • A guardrails, evaluation & LLMOps layer so quality holds over time.
Governed RAGAI agentsCoding copilotsGuardrailsEvaluation & LLMOps
AI · 03 / Accelerated modernization & reinvention

Speed up legacy upgrades — with evidence at every step.

AI is genuinely changing modernization economics: code that took years to understand and replace can now be mapped, documented, tested, and migrated in months. We apply that leverage where it is safe — behind test-driven guardrails and senior review — so you get the speed without the risk a regulated platform cannot absorb.

When to call us

  • A core Java or COBOL platform is too costly, or too risky, to keep as-is.
  • A "big-bang rewrite" has stalled — or the risk committee won't approve one.
  • Undocumented legacy logic blocks nearly every change you try to make.
  • You need to modernize fast but cannot compromise auditability.

What you get

  • AI-driven code comprehension, dependency maps, and documentation.
  • Test-driven migration: AI-generated regression nets that prove behavior.
  • Assisted translation & refactoring (COBOL / legacy Java → modern services).
  • Incremental, human-validated cutover — no unverifiable leaps.
01

Understand

AI maps dependencies and extracts the business logic buried in legacy code.

02

Prove

We generate a regression-test net that pins down current behavior — your safety net.

03

Transform

Assisted translation and refactoring produce modern services that must pass those tests.

04

Validate

Senior engineers review and cut over incrementally, with full audit trails.

Code comprehensionTest-driven migrationCOBOL → JavaRefactoringIncremental cutover

Every AI engagement is built to be governed. Model validation, monitoring, data lineage, and human oversight aligned to OSFI E-23, PIPEDA, and Quebec Law 25 — with sovereign and Canadian data-residency options. We design for the regulation that's here and the regulation that's coming, and we never ship autonomy you can't explain to an auditor.

What we deliver

Four more practices, one senior delivery team.

01 / Application Development

Java, Spring, and cloud-native engineering

Production Java/JEE systems, microservice decomposition, event-driven architectures, API platforms, and the migration work to bring a 10-year-old monolith into the present.

  • Greenfield Java/Spring Boot services and platforms
  • Monolith decomposition and strangler-fig migrations
  • API design, gateway and service-mesh patterns
  • Event-driven systems on Kafka, Pub/Sub, Kinesis
  • Containerization and Kubernetes operationalization

What you get → a faster, safer release cadence and a codebase your team can confidently own.

02 / Cloud & Architecture

Migration, platform design, and operations

Reference architectures across AWS, Azure, and Google Cloud — designed to survive an audit and a 3 a.m. incident. Infrastructure as code, observability and security by default.

  • Cloud migration assessments and target-state architecture
  • Landing-zone, identity, and network design
  • IaC with Terraform, Pulumi, and native cloud tooling
  • CI/CD, GitOps, and progressive delivery patterns
  • Observability stacks: metrics, logs, traces, SLOs

What you get → a governed cloud platform that survives an audit and a 3 a.m. incident — repeatable, observable, and cost-aware.

03 / Data & Analytics

Lakehouse, streaming, BI, and ML-ready data

Modern data platforms designed for the regulatory and reporting needs of banking, insurance, and public-sector clients. Lineage, governance, and quality treated as first-class concerns.

  • Lakehouse architecture on Databricks, Snowflake, and open formats
  • Streaming pipelines on Kafka, Spark Structured Streaming, Flink
  • BI & reporting platforms with auditable lineage
  • Data quality, governance, and metadata management
  • ML and AI-ready feature stores and serving infrastructure

What you get → trusted, lineage-aware data your teams and your auditors can rely on for reporting, analytics, and AI.

04 / Delivery & Consulting

Solution design, project management, integration

The discipline that keeps everything else on track — clear scope, weekly demos, transparent burn-down, and stakeholder reporting that doesn't waste anyone's time.

  • Solution architecture and target-state design
  • Project management and program coordination
  • System integration across legacy and modern stacks
  • Production support, SRE, and incident response
  • Senior talent placement for short-term gaps

What you get → clear scope, weekly proof, and a project that lands on time — without the delivery surprises.

How we work

Four phases, transparent at every step.

Phase 01

Discover

Stakeholder interviews, system inventory, constraint mapping. We come back with a clear scope and a candid view of risks before any code is written.

Phase 02

Design

Target-state architecture, component diagrams, decision records. A document your engineers and your auditors can both read.

Phase 03

Build

Iterative delivery in two-week increments. Weekly demos, shared backlog, working software at the end of every sprint.

Phase 04

Operate

Knowledge transfer, runbooks, on-call handover. We leave you with a system your team can run without us — and we'll be there if you need us.

FAQ

The questions regulated buyers ask first.

How do you handle confidentiality and NDAs?

We work under your NDA as standard — it's why most of the case studies on this site are anonymized. Client code, data, and documents stay inside your environment and your cloud accounts; we work in your repos and under your access controls, not ours.

Where does our data live? Can AI stay in-country?

Yes. We design for Canadian data residency and can deploy AI on sovereign or in-VPC infrastructure — AWS and Azure Canadian regions, or self-hosted open-weight models for air-gapped and highly sensitive workloads — so regulated data never leaves your control. Data residency and sovereignty are scoped explicitly at the start of every AI engagement.

How do you keep AI audit-ready and compliant?

Every model and agent ships with validation, monitoring, data lineage, and human-in-the-loop checkpoints aligned to OSFI E-23 model-risk expectations and your privacy obligations (PIPEDA, Quebec Law 25). We design for the regulation that's here today and the regulation that's coming — and we won't ship autonomy you can't explain to an auditor.

We've been burned by a big-bang rewrite. How is your modernization different?

We favour incremental, test-driven migration over rewrites. AI maps and documents the legacy system; we generate a regression-test net that pins down current behaviour; then we migrate service by service behind that safety net, cutting over only what passes. There are no unverifiable leaps, and you can stop or re-sequence at any point.

You're a small, senior-led firm — how do you scale and de-risk delivery?

You get senior practitioners from day one, not a staffing pyramid. For larger programs we assemble a vetted senior network while staying accountable as your single point of technical ownership. Everything is documented, observable, and automated so the work doesn't depend on any one person — including us.

What happens at the end of an engagement?

Knowledge transfer, runbooks, observability, and automation are treated as delivery outputs, not afterthoughts. We leave you with a system your own team can run with confidence — and we stay available if you want ongoing support.

Get in touch

Have a project in mind? Let's talk.

Tell us the system, the timeline, and the outcome. We'll come back with a candid view in a few business days.

Start a conversation
Phone   +1 (416) 880-6899
Email     jeeleon@gmail.com
LinkedIn  /in/jeeleon
Office    Markham, ON, Canada