Managed AI Services: Run the Right AI Model, Under Control
We audit your business processes and data, select the right AI model for each workflow, then build secure AI systems and run them in production for you. Claude, GPT, Gemini, or a private LLM deployment inside your own environment, always kept current.
Is Managed AI Services right for you?
You need Managed AI Services when AI is business-critical and one of these is true:
What you get with Managed AI Services
One Managed AI Services subscription. One team that owns your AI operations in production, measured on your KPIs.
What’s included | What it means for you |
|---|---|
| AI model selection and deployment | The right model for each workflow, in the cloud, hybrid, or on-prem |
| Agentic systems in production | Autonomous agents with guardrails and clear human handoffs |
| AI governance and model monitoring | Continuous testing, data security, and monitoring of behavior and cost |
| Continuous ModelOps and upgrades | We switch to a better model the day it qualifies, with no re-scoping |
How does Managed AI Services work?
Every engagement starts with Discovery: a business process and data audit, so every AI decision after it is based on evidence.
Discover:
We audit your workflows and data, then agree on priority workflows, KPIs, and a roadmap.
Design & Select:
Deployment architecture and AI model selection for each workflow.
Implement:
Agents built into your environment, with guardrails and human handoffs.
Control & Upgrade:
Continuous ModelOps, AI model monitoring, cost optimization, and model upgrades.
Start with Discovery
We audit your business processes and data, and you get a prioritized list of AI workflows,
a data readiness assessment, KPIs for each workflow, and a roadmap.
The right AI model, in any environment
Our AI model management is model-agnostic: we don’t push one vendor.
For every workflow, we pick the model tier that fits your outcome, data rules, and budget.
| Model tier | Examples | Best when | Where it runs |
|---|---|---|---|
Frontier commercial | Claude GPT-5 Gemini | You need the strongest reasoning or agentic coding | Cloud, or private networking via AWS Bedrock, Azure OpenAI, Google Vertex |
Open weight | Llama Nemotron Granite gpt-oss | Data must stay inside your boundary, or volume makes APIs costly | Your cloud, hybrid, or on-prem |
Fully open source | OLMo | Regulators need to inspect training data | Anywhere, including air-gapped |
Decision models | Jev OpenAI Decisions API | A workflow needs instant, repeatable choices from a fixed set of options | Cloud API, working alongside any of the tiers above |
Why First Line Software?
Without
AI disconnected from business goals
Locked into one model vendor
One-time setup, stuck on last year’s model
No visibility into AI behavior or cost
With FLS Managed AI Services
AI tied to your KPIs from day one
Model-agnostic across frontier, open-weight, and open-source
Upgrades to better models included
Real-time monitoring of quality, grounding, and cost
FAQ
Is Managed AI Services (MAIS®) model-agnostic?
Yes. We work across frontier models such as Claude and GPT-5, open-weight models such as Llama, Nemotron, and Granite, and fully open-source OLMo. We choose the model per workflow based on your outcome, data constraints, and cost, not on a single vendor partnership.
Can you run an LLM on-premise or in our own cloud?
Yes. Open-weight and open-source models can run in your cloud tenant, in a hybrid setup, or fully on-premise, including air-gapped environments, so your data never leaves your boundary. Frontier models run through enterprise agreements such as AWS Bedrock, Azure OpenAI, or Google Vertex.
What happens after Discovery?
You get a prioritized list of AI workflows, a data readiness assessment, KPIs, and a roadmap. From there, we design the architecture, select the models, and move the first workflows into production under a Managed AI Services subscription.
What happens when a better model is released?
We switch you to it once it qualifies, without re-scoping the engagement. Our AI Lab benchmarks new models and agent harnesses continuously, and upgrades are part of the subscription, not a new project.
Start with a business process and data audit
Find out where AI will pay off, what your data can support, and which workflows to move first.
Book a Discovery