Google Cloud implementation for teams already on GCP
We add qualified Google Cloud delivery capacity where it matters:
BigQuery, Vertex AI / Agent Platform, data engineering and any integration layer with ERP, CRM and operational workflows.
Understand your fit quickly. We propose a delivery model and tell you whether we can help.
5 Google Cloud-qualified engineers for data / ML / cloud
- Professional Data Engineering and Machine Learning capability
- Fixed-scope delivery or embedded capacity
- Senior-led architecture and integration
- EU working-day overlap with structured handoff for U.S. teams
What our team has already shipped
Behavioral analytics at 100K+ player scale
High-volume financial document scoring
Quoting connected to operational data
Connect to the systems that run your business
BigQuery & data platforms
Vertex AI & GenAI
ERP / CRM integration
Cloud Run / GKE / platform
Automation & RevOps
Production discipline
Three ways to add Google Cloud delivery capacity
| Direct hiring | Large consultancy | OPTI | |
|---|---|---|---|
| Best fit | Permanent internal capability | Large programmes with broad governance | Focused GCP delivery gaps and integration-heavy work |
| Commercial model | Full employment cost | Consulting programme / enterprise framework | Fixed scope or embedded capacity |
| Team shape | One role at a time | Broader mixed consulting team | Small, senior-led, GCP-qualified team |
| Where knowledge lives | Internal by default | Depends on programme structure | Client repositories, documentation and explicit handover |
| Typical advantage | Long-term ownership | Scale and programme breadth | Speed, focus and cloud-to-business |
Senior-led delivery
Past cloud, into your process
Built for mid-market complexity
Take the outcome, or add the capacity
Fixed-scope Delivery
- assessment: sources, systems, KPI and data contract
- pilot on your data
- documentation and handover
- optional managed support and cost monitoring
Embedded GCP capacity
- work inside your procedures
- scale capacity according to the agreed allocation
- knowledge stays in your team; delivery is documented
- senior-led technical oversight
Quick Questions
Do you work with our existing team or replace it?
We normally complement the existing team. OPTI can own a defined outcome end to end or embed qualified capacity into your delivery model while your team keeps product ownership, rituals and architecture decisions.
What about IP and data security?
NDA-based work is standard. We work with least-privilege access, clear repository and environment ownership, and delivery discipline aligned with our ISO 27001 and ISO 9001 certifications. IP ownership is defined contractually and can remain fully client-controlled.
What is the minimum engagement?
We do not position this as isolated ad-hoc hours. Small fixed-scope work normally starts with a scoped assessment or sprint. Embedded capacity is agreed by role, allocation and expected duration after the technical assessment.
Do you only work on Google Cloud?
This campaign is intentionally Google Cloud focused. In production, the work often reaches beyond GCP into ERP, CRM, ecommerce, document systems and custom APIs. That integration layer is one of the reasons clients use OPTI.
How quickly can you start?
We confirm a realistic start window after the technical assessment, based on scope, access requirements and current capacity. When capacity is open, onboarding can be materially faster than permanent hiring, but we do not promise a fixed start date before we understand the work.
What technologies and methodologies are involved?
Technologies: Google Cloud, BigQuery, Vertex AI, Agent Platform, Cloud Run, GKE, Looker Studio, ERP, CRM, RAG, document intelligence, CI/CD, observability
Methodologies: 30-minute technical assessment, delivery-gap scoping, selection between fixed-scope delivery and embedded capacity, confirmation of resources and access, integration into client procedures and repositories, documented handover.