Engineering organisation built for production reality
BlackLake is a boutique technology firm that combines AI, automation, and platform engineering under a single disciplined operating model.
We exist because modern systems become slow, fragile, and expensive when growth outpaces discipline. Teams inherit complexity without baselines. Automation accumulates without observability. AI gets bolted on without evaluation. BlackLake brings clarity, speed, and control back to production.
Operating principles
How BlackLake works
These aren't values on a wall — they're constraints that shape every engagement.
Depth over volume
Fewer engagements, deeper work. Surface-level delivery creates surface-level outcomes.
Constraints before design
Define what cannot break — budgets, SLAs, compliance — before designing what changes.
Baselines before change
Measure latency, cost, and failure modes. Ship behind guardrails with explicit rollback.
Operations is delivery
Runbooks, alerts, and ownership are part of the work. If it can't be operated, it's not finished.
Domains
Intelligence · Systems · Product
Three domains, one method. Each is grounded in the same discipline: constraints first, baselines measured, operations built in.
Systems that understand
Applied AI with evaluation, constraints, and known failure modes. Models connected to production with the same rigour as any other system.
- Retrieval-augmented generation with guardrails
- Constrained generation products
- Evaluation frameworks and regression testing
Automation that scales
Cloud architecture, data pipelines, and platform reliability — with observability, cost control, and operational clarity built in.
- Event-driven architectures
- Pipeline modernisation and migration
- Reliability engineering and SLOs
Tools that endure
Internal platforms, operator tooling, and interfaces designed to reduce toil and remain maintainable.
- Internal tools and dashboards
- Workflow automation
- Developer experience
Engagement model
Blueprint → Build → Calibrate
A structured progression from discovery to delivery to ownership. Each phase has defined outputs and clear handover.
Fixed-scope discovery that makes constraints explicit.
- System map and baseline metrics
- Risk register with guardrails
- Sequenced delivery plan
Implementation with controlled change.
- Baselines before changes
- Rollback paths and feature flags
- Runbooks and ownership handover
Stewardship until internal ownership.
- SLOs, alerts, and regression controls
- Performance and cost budgets
- Exit to internal rhythm
Track record
Measured outcomes from production
Representative outcomes from production engagements. Specifics anonymised to preserve confidentiality.
Start with a Blueprint
Share context and constraints. If it's a fit, the next step is a Blueprint: a short, paid engagement that produces a scoped plan, risk register, and delivery sequence.