85% cost reduction in speech-to-text with managed AI on AWS
See how managed operations and architecture tuning delivered measurable savings.
- Major efficiency gain on production speech workloads
We keep your AI secure, efficient, and performing at scale.
GenAI Projects
Clients
POC Conversion in 2025
Managing AI in production is complex. Models drift, performance changes, costs fluctuate, and compliance requirements evolve.
Firemind's Managed AI service ensures your generative AI workloads are secure, efficient, and optimised, so you can focus on delivering business outcomes, not firefighting technical issues.
What you get:
Our Managed AI ensures your generative AI evolves alongside your business, adapting to changing needs and opportunities giving you a sustained competitive advantage powered by high-performing AI.
Need continuous oversight without building a large in-house SRE function?
Managed AI gives you the operating model to run models safely at scale.
We embed with your teams to run models, pipelines, and guardrails as a managed service.
We document current workloads, SLAs, data boundaries, and cost drivers - then agree operating metrics.
Monitoring, incident response, drift detection, and cost optimisation run continuously against agreed guardrails.
Regular reviews translate telemetry into roadmap items - model updates, fine-tuning, or architecture changes.
You gain:
Proven delivery
Examples of optimised, governed AI operations.
See how managed operations and architecture tuning delivered measurable savings.
Managed AI is an ongoing service where Firemind operates your AI infrastructure in production. Once your AI systems are live, we handle monitoring, performance management, model updates, cost optimisation, and incident response. Your team doesn't need to become AI infrastructure specialists to keep things running well.
We manage the infrastructure your AI workloads run on: compute, storage, APIs, model serving, and integration layers. We monitor performance, track model drift, manage costs, and respond to issues before they affect your users. We agree the scope upfront. You always know what we cover and what remains with your team.
The AI Build Sprint is for building and validating. It's a time-limited engagement that delivers production-ready AI solutions. Managed AI is what comes next: the ongoing operational support for those solutions once they're live. Some organisations use both in sequence. Others come to Managed AI after building AI capabilities through a different route.
We support AI workloads running on AWS, Azure, and Google Cloud. This includes large language model deployments, ML inference pipelines, data processing workflows, and API integrations with third-party AI services. If you're unsure whether your setup falls within scope, the right starting point is a short conversation with our team.
We will review your current stack and propose a Managed AI scope matched to your risk profile.
A 20-minute focused session on your goals and current situation.
A clear plan and scope tailored to your priorities.
No obligation - move forward when the time is right.
No obligation - just a focused 20-minute discussion about your goals.