--- title: "From manual to managed: How Isos streamlined API access across LLMs" description: Isos Technology built a scalable, policy-based AI API governance framework using Jira Service Management and LiteLLM. Accelerate AI access, eliminate expense reporting, and control usage across OpenAI, Claude, and more. --- [Blog - Isos Technology ](https://blog.isostech.com) # [From manual to managed: How Isos streamlined API access across LLMs](https://blog.isostech.com/from-manual-to-managed-how-isos-streamlined-api-access-across-llms) Written by [Danielle Paula](https://blog.isostech.com/author/danielle-paula) | May 23, 2025 While most companies are still figuring out how to apply large language models (LLMs) like OpenAI, Claude, or Hugging Face, a quieter challenge is emerging behind the scenes: **managing how teams access and use these tools—safely, consistently, and at scale**. At Isos Technology, we saw this coming early. As we embedded AI into internal workflows—from Atlassian Intelligence and GPTs to orchestration via Rovo and n8n—we realized something important: ***AI API sprawl wasn’t a future problem. It was happening already.*** So, we built a centralized, policy-driven framework to manage AI API tokens across the company. And now, we’re helping clients do the same. ## The problem: Rapid AI adoption without guardrails AI access typically starts organically—developers testing GPT-4, business users experimenting with Claude. But it quickly spirals into something much harder to manage: - Personal tokens used without IT oversight - No attribution of API usage to teams or cost centers - Tokens lingering far past expiration - Premium models used for basic tasks - Manual token provisioning and renewals - Employees submitting expense reports for API keys - Managers manually reviewing and reimbursing token spend Sound familiar? It’s the same governance gap we saw in early cloud and SaaS adoption—**innovation racing ahead while policy, security, and accountability struggle to catch up**. ## The Isos solution: Centralized token management built for scale To solve this, we designed and implemented an internal platform that manages AI API access like any mission-critical service: with policy, automation, and full lifecycle control. ### Self-service access through Jira Service Management We used Jira Service Management (JSM) to create a streamlined request-and-issue workflow for tokens. Every request includes: - The requester and their team - The intended LLM(s) (e.g., OpenAI, Claude) - The business use case and expected duration Once submitted, tokens are provisioned automatically using custom **30, 60, or 90-day expiration rules**—no manual approval required. #### What changed? *Provisioning went from a **2–3 hour manual process** to an **automated flow taking just 1–3 minutes**.* Plus, because tokens are provisioned internally, there's **no need for employees to buy access and submit for reimbursement**—a huge win for both team members and managers. ### Unified model access with LiteLLM To avoid vendor lock-in and reduce complexity, we integrated [**LiteLLM**](https://docs.litellm.ai/) as the backend routing layer. With LiteLLM, we can: - Route a single request to the most cost-efficient or capable model - Abstract away provider-specific quirks - Apply consistent logging, rate limits, and authentication policies - Support **multi-model access** through a unified interface *Pro tip: Native providers like OpenAI don’t offer this. LiteLLM acts as our secure gateway, enabling centralized control across multiple vendors.* ### Real-time visibility into usage and ownership Every token is now linked to a: - User - Team - Business purpose - Cost center This lets us: - Attribute costs to specific projects or clients - Forecast future usage trends - Analyze ROI for internal R&D or billable work Finance and delivery teams can plan confidently—without chasing down who used what and why. ### Centralized admin dashboard for IT governance IT controls the full token lifecycle through a centralized dashboard: - Review or revoke access - Enforce Acceptable Use Policies - Monitor token activity - Track upcoming expirations - Prevent duplication and key misuse We didn’t just solve a problem—we built a scalable foundation for **enterprise-grade AI access**. ## Measurable results: Smarter access at speed This isn’t a “cost savings” story. It’s a **scale story**—one built on automation, visibility, and smarter workflows. | Metric | Before | After | | --- | --- | --- | | Provisioning time | 2-3 Hours | Instantaneous  | | Expiration enforcement | Manual | Fully automated | | API usage availability | Fragmented | Centralized, real-time | | Token cost reconciliation | Manual expense reports | Integrated into IT-managed platform | | Manager approval workload | Frequent review of token expenses | Eliminated via automated workflows | Employees no longer submit expense reports for AI API tokens. Instead, tokens are issued through a governed internal platform, saving **manager time**, reducing **finance workload**, and eliminating **reimbursement delays**. ## Why it matters for you Whether you’re just starting with LLMs or running production-scale AI apps, **access governance is non-negotiable**. Without it, you risk: - Skyrocketing API bills - Security gaps from unmanaged keys - Silos and duplication - Slow, inconsistent access for employees - Time-consuming manual expense workflows With it, you gain: - Speed - Security - Visibility - Control - Process automation and operational efficiency ## What industry leaders are saying Your instincts aren’t wrong—governance is the next frontier in AI maturity. Just ask the experts: - **Gartner**: AI cost planning must include governance, not just model performance or pricing. - **Forrester**: Enterprises need structured AI governance to build scalable AI capability. - **McKinsey**: Organizations with executive oversight of AI governance outperform on bottom-line results. - **Microsoft Azure**: Now offers native generative AI API gateways—because token control is critical. ## Is this right for you? This solution is ideal for mid-size to enterprise organizations that are: - Scaling AI across departments - Working with multiple model providers - Embedding AI into core workflows - Looking to bring governance and visibility to their AI infrastructure - Tired of manual approvals, expense reports, and unmanaged API usage ## Let’s build the foundation for enterprise AI—together Isos didn’t wait for chaos. We built clarity into our AI operations from day one. Now we’re helping clients do the same—with a governance framework that gets teams what they need quickly, **without giving up control**. 📞 [**Book a Free Strategy Session with Isos Technology**](https://chatgpt.com/g/g-ZQSTWEp88-ghostwriter-pro/c/68236b5e-dee4-8001-8c6e-e56964760e7f#) Let’s explore how we can help you scale AI access—securely, efficiently, and without the sprawl.   [View full post](https://blog.isostech.com/from-manual-to-managed-how-isos-streamlined-api-access-across-llms) ```json { "@context" : "http://schema.org", "@type" : "BlogPosting", "author" : { "@type" : "Person", "name" : "Danielle Paula" }, "dateModified" : "2025-10-17T17:42:11.147Z", "datePublished" : "2025-05-23T20:22:06Z", "headline" : "From manual to managed: How Isos streamlined API access across LLMs", "image" : { "@type" : "ImageObject", "height" : 768, "url" : "https://go.isostech.com/hubfs/AI-Generated%20Media/Images/An%20image%20evoking%20this%20idea%20While%20most%20companies%20are%20still%20figuring%20out%20how%20to%20apply%20large%20language%20models%20LLMs%20like%20OpenAI%20Claude%20or%20Hugging%20Face%20a%20quieter%20challenge%20is%20emerging%20behind%20the%20scenes%20managing%20how%20teams%20access%20and%20use%20these%20toolssafely%20co-3.jpeg", "width" : 1344 }, "mainEntityOfPage" : "https://blog.isostech.com/from-manual-to-managed-how-isos-streamlined-api-access-across-llms", "publisher" : { "@type" : "Organization", "logo" : { "@type" : "ImageObject", "height" : 60.0, "url" : "https://go.isostech.com/hubfs/isos%20tech%20logo%20small.png", "width" : 86.4 }, "name" : "Blog - Isos Technology" } } ```