Install the delivery system. Modernize the platform. Harden the edge cases.

What it is

A delivery system that uses AI agents to accelerate coding, refactoring, test generation, documentation, and PR review—wrapped in enterprise-grade quality controls.

When to use

You want 2–5× faster throughput without reliability or security regression.

Deliverables

• Agent workflow design (coding/refactor/test/doc/review loops)
• Quality gates + definition of done
• Evaluation harness (golden tests + regression)
• CI/CD integration and guardrails

Typical engagement

2–4 weeks to install the system; ongoing coaching optional.

What it is

Connector-first architecture that makes data movement reliable, observable, and safe to run at scale.

When to use

You need integrations that can handle auth complexity, retries, batching, and governance.

Deliverables

• Connector architecture patterns (auth, retries, batching, CDC where applicable)
• Orchestration and data contracts
• Governance: lineage, access controls, retention

Typical engagement

3–8 weeks depending on integration complexity and governance requirements.

What it is

A trustworthy analytics layer that aligns product decisions, operations, and AI systems on shared metrics.

When to use

You need a semantic model, performance tuning, and quality checks before scaling analytics usage.

Deliverables

• Metrics layer / semantic model
• Dashboarding strategy and performance tuning
• Data quality checks + anomaly detection hooks

Typical engagement

2–6 weeks for a focused metrics foundation and initial dashboards.

What it is

Modernization that reduces risk through incremental replacement patterns instead of risky big-bang rewrites.

When to use

You need to replace legacy systems while keeping business continuity and reducing operational risk.

Deliverables

• Target architecture + migration roadmap
• Decomposition plan (services/modules), API strategy
• Observability, reliability, scaling plan

Typical engagement

4–12+ weeks depending on the number of systems and migration constraints.

What it is

Engineering practices that embed security controls into SDLC and system design so compliance readiness becomes a byproduct of delivery.

When to use

You need credible answers for security review and controls that engineering can sustain.

Deliverables

• Security architecture: least privilege, secrets, audit logs
• Control mapping into engineering workflow
• Evidence-ready operational practices (runbooks, incident readiness)

Typical engagement

2–8 weeks for control mapping, system changes, and evidence-ready workflows.

What it is

Production-grade financial workflows with a focus on risk-aware funding, order lifecycles, and auditable data models.

When to use

You want to build or harden trading, funding, or financial planning systems without reinventing regulated flows.

Deliverables

• Plaid linking + bank auth + ACH funding flows (risk-aware)
• Alpaca order lifecycle, portfolio & performance tracking
• Auditable ledger-style data model and reconciliation strategy

Typical engagement

3–10 weeks depending on scope, risk posture, and audit requirements.