Organisations rushing to embed generative AI are discovering a structural problem. Every integration creates dependency. Once a model is wired into a core system, switching becomes costly. Worse, upgrades are no longer optional, each innovation cycle demands a rebuild, making AI feel brittle just when it should be a source of agility.
Instead of hard‑coding AI directly into platforms, businesses are starting to separate the model layer from the application layer. That separation allows teams to test, compare and switch models without disturbing the systems that depend on them.
With this approach, governance improves by design. Access policies apply across models, not just per vendor. Data can be anonymised, routed and audited independently of which engine is processing it. Models become plug‑and‑play components, managed through configuration rather than code. It also means enterprises can deploy multiple models side by side, using the right engine for each task rather than forcing a single generalist to do everything.
Cerillion is positioning itself at the centre of this architectural shift. Its AI orchestration framework abstracts the complexity of working with multiple models, enabling clients to build once and adapt continuously.
Cerillion plc (LON:CER) is a leading provider of billing, charging and customer management systems with more than 20 years’ experience delivering its solutions across a broad range of industries including the telecommunications, finance, utilities and transportation sectors.
