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Scaling AI with project-based DataOps looks good at first, but won’t hold up for long.
As organisations rapidly scale their data and AI initiatives, many are discovering that short-term, project-based approaches to DataOps no longer deliver the stability, agility, or ROI they need. Instead, there’s a growing shift toward long-term platform stewardship - a model that prioritises sustainability, continuous improvement, and strategic enablement.
This evolution is being driven by the rising importance of sustainable AI and data management, particularly for fast-scaling businesses in complex or highly regulated industries where innovation must be balanced with governance and cost-efficiency.
At the heart of this shift is a new approach, a model built for resilience, scalability, and long-term success: Evergreen DataOps.
Traditional DataOps projects are often reactive, siloed, and narrowly scoped. Once delivered, these data systems frequently fall into disrepair due to a lack of ownership, governance, and continuous improvement.
Steven Sell, Chief Operations Office at Colibri Digital explains that many organisations "ingest all their data without defining the business problems to be solved”, leading to bloated platforms full of irrelevant or unused data.
These legacy approaches:
In industries like healthcare, finance, and transport, where compliance with GDPR, ISO, SOC 2, and other regulations is non-negotiable, the costs of poor data governance multiply rapidly.
Steven said: “Even with advanced data tools, businesses still need strong logic, security, and governance layers. Essentially, without strong logic and governance, it’s like putting a jet engine on a paper plane. The data layer should be seen as a full architectural solution, not just a place to store data.”
Many project-based DataOps efforts also fail because they are technology-first, not business-first. Without a clear business question or objective, teams often ingest vast amounts of irrelevant data, creating complexity, bloated costs, and unmanageable data lakes. A platform is only valuable if it’s solving real problems.
Evergreen DataOps means treating your data platform like a living product - not a one-and-done project. It’s about ongoing tuning, governance, and cost control so it grows with your business. Instead of delivering once and moving on, Evergreen DataOps continuously evolves and improves platforms to support business growth, innovation, and sustainability.
Evergreen DataOps offers significant benefits for enterprise AI, ensuring data pipelines are continuously up-to-date, reliable, and automated. This approach minimises technical debt and manual intervention, enabling faster deployment of AI models and more agile decision-making.
So, what’s in it for you?
Steven said: “We help customers reinvest the ROI from early optimisations into future AI and ML initiatives, creating a flywheel of innovation and value. Adopting policies for data retention, archiving, and FinOps is also recommended as part of an evergreen strategy, especially if sustainable AI and fine-tuning your systems to efficiency are priorities.”
Some organisations assume Evergreen DataOps is complex or costly to adopt. In reality, many businesses can start small by:
Steven commented: “Not every business has the internal expertise to run complex data journeys. That’s why we recommend managed services with built-in consultancy to ensure success from day one. We also understand that building a business case for this can be difficult. One way to overcome resistance to Evergreen DataOps is to start small via proof of concepts or minimum viable platforms, lowering risk and building internal buy-in while proving early value.
“We always suggest working with unbiased, vendor-agnostic advisors to align on relevant use cases before scaling up.”
Regulated industries face added pressure to comply with evolving data privacy, auditability, and security standards. In these industries, compliance isn’t just a box to tick - it’s the concrete your entire platform is built on.
Evergreen DataOps ensures:
In sectors like financial services and healthcare, clients have achieved hundreds of thousands in cost savings by modernising to evergreen, serverless architectures while maintaining full compliance and unlocking new innovation potential.
Steven said: “Security and compliance aren’t bolt-ons with Evergreen DataOps - they’re baked into the foundation. You can’t scale trust without them. You must include built-in security, access control, and data sharing policies to meet frameworks like GDPR, ISO 27001, and SOC 2.”
Starting with Evergreen DataOps unlocks faster scalability, smoother integration of emerging technologies, and more predictable operational performance.
For PE-backed companies, it also offers:
“When your AI journey starts with sustainability and business alignment, you scale faster and smarter”, said Steven.
At Colibri, we’ve designed our Evergreen Data & AI Ops model to help organisations take the leap from fragmented projects to strategic platforms.
Key pillars of our approach include:
Steven comments: “We’ve helped clients save hundreds of thousands - even millions - by enabling smarter data platforms that grow with their business.”
Looking ahead, Colibri is actively integrating AI and ML into the core of our managed services, enabling platforms to become self-healing, auto-optimising, and deeply intelligent. This allows IT teams to focus on strategy, while automation handles much of the day-to-day ops.
The future of enterprise AI depends on strong, adaptive data foundations. Evergreen DataOps empowers businesses to:
If you're rethinking your AI and data platform strategy, Colibri’s evergreen model can guide you through the transition. We’ll ensure you're set up for today’s success and tomorrow’s growth.
Ready to ditch the data drama and build something that lasts? Let’s chat - your evergreen AI future starts with one conversation.
Evergreen DataOps for PE-backed organisations supports rapid growth by keeping data platforms scalable, cost-efficient, and ready for change. This is ideal for fast-moving, high-return environments.
Project-based delivery stops at launch while evergreen keeps evolving and optimising for performance, cost, and governance long after go-live.
For regulated industries, Evergreen DataOps bakes in compliance from the start, with ongoing monitoring to meet data, security, and audit standards - no bolt-ons needed.
Getting on board with Evergreen DataOps early in your AI journey gives you a future-ready platform that’s scalable, optimised, and easier to adapt as tech and business needs evolve.
Absolutely. Evergreen DataOps scales to fit your size, offering sustainable growth without the typical project headaches.
By continuously tuning performance and automating the boring stuff, Evergreen DataOps keeps your AI fast, lean, and ready to grow. It makes scalability a real possibility – no more legacy tech debt or cumbersome tools holding you back.
Change takes effort and that still rings true when transitioning from a project-based to platform-based approach. The key challenges are adopting a new mindset, upfront investment, and cross-team coordination. But the long-term payoff is huge.
Evergreen DataOps helps with cost efficiencies by cutting waste, automating routine work, and helping you spend smarter by prioritising what actually drives value.
Platform stewardship is all about ongoing care - monitoring, improving, and aligning the platform to your goals as they evolve.
Plan for scalability, commit to ongoing optimisation, align with business goals, and bring in the right expertise to guide the journey.
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