Engineering across the stack, the org and the roadmap
Four services that are deliberately adjacent. Most engagements start in one and pull in another once the integration surface becomes obvious.
Full-stack solutions
Product engineering end to end — web apps, APIs, data models and the cloud they run on. One team from schema to ship.
- TypeScript
- Next.js
- Node.js
- Python
- PostgreSQL
- AWS
- Terraform
Typical outcomes
- Replace fragile internal tooling with a system your team can extend
- Take a validated prototype to a production-grade platform
- Cut page loads and job runtimes that are costing you customers
What you get
- Architecture and data model you own
- Typed APIs with contract tests
- CI/CD, infrastructure as code, observability
- Runbooks and handover documentation
Salesforce solutions
Implementation, custom development and rescue work across Sales, Service and Experience Cloud — built to survive the next admin.
- Apex
- LWC
- Flow
- SOQL
- MuleSoft
- Salesforce DX
Typical outcomes
- Untangle an org that has grown past its original design
- Connect Salesforce to the rest of your stack without nightly CSVs
- Replace manual ops with governed, tested automation
What you get
- Org assessment with a prioritised remediation plan
- Apex and Lightning Web Components under test coverage
- Integration layer to your product, ERP and warehouse
- Deployment pipeline with sandbox-to-prod promotion
AI integrations
LLM features wired into real systems — retrieval over your own data, agents with guardrails, and evaluation so you can trust the output.
- Claude
- LangGraph
- pgvector
- Python
- TypeScript
- Snowflake
Typical outcomes
- Answer internal questions from your documents instead of tribal knowledge
- Automate review and classification work that scales with headcount today
- Ship an assistant your compliance team will actually sign off on
What you get
- Retrieval pipeline over your sources with access control preserved
- Evaluation harness and regression suite for prompts and tools
- Cost, latency and fallback budgets per feature
- Human-in-the-loop review paths and audit logging
Staff augmentation
Engineers who join your team, not a black-box vendor. Same standups, same board, same definition of done.
- Frontend
- Backend
- Salesforce
- Data
- DevOps
- AI/ML
Typical outcomes
- Add senior capacity without a six-month hiring cycle
- Bring in Salesforce or AI specialists for one phase of the roadmap
- Keep delivery moving through parental leave, attrition or a crunch
What you get
- Shortlist of vetted engineers within a week
- Two-week ramp-up with a named delivery lead
- Your tooling, your process, your code review
- Monthly rolling terms — scale up or down
Buy an outcome, a team, or a second opinion
The same engineers, three commercial shapes. Start in one and move to another when the work changes — most clients do.
Project delivery
A sized, outcome-owned build. We scope the work, ship in two-week increments and hand over documented, tested code.
- Discovery sprint
- Fixed or capped scope
- Dedicated squad
Best forNew products, replatforms, fixed-scope modules
Staff augmentation
Vetted engineers embedded in your team, your tooling and your standups — scaling up or down as your roadmap moves.
- Monthly per engineer
- Your process and tools
- 2-week ramp-up
Best forCapacity gaps, specialist skills, long roadmaps
Advisory retainer
Architecture review, Salesforce governance and AI feasibility work for teams who need senior judgement, not more headcount.
- Capped hours
- Written recommendations
- Rolling monthly
Best forAudits, platform decisions, AI roadmaps
Not sure which of these you need?
Describe the problem and we will tell you which service fits — or that it is not one we should take on.