Executive Summary
A growing technology organization, with distributed teams across the U.S. and India, wanted to move beyond a small, engineering-only group building proofs of concept and reach a much broader population of employees. Fission Labs deployed CodeVector, a governed middleware gateway between coding assistants and AI model providers, to extend AI-assisted development beyond the core 15-person engineering team.
Over a one-month rollout, the organization grew its AI-enabled population to roughly 45 employees, a 3x increase, cut time to market by at least 30 days, and reduced monthly AI tool spend by 85% in the process.
Business Challenge
Product development and proof-of-concept work were bottlenecked by a small engineering team, with no practical way to let non-engineering employees contribute using AI coding tools.
- Individual subscriptions, at roughly $20 per employee per month, made broad rollout expensive and impractical to justify without knowing who would actually use them.
- The organization had no visibility into actual token usage, no way to control cost or model access by individual or group, and no governance layer to support extending access safely to a much larger and less technical population.
Technical Solution
Fission Labs deployed CodeVector as a middleware proxy layer between coding assistants (Claude Code, Cursor, and others) and AI model providers, acting as both a provider to the coding assistant and a customer to the underlying models.
- Being provider-agnostic, CodeVector connected the organization to 9 models across 4 different providers from a single interface, avoiding dependency on any one vendor.
- Pay-as-you-go access, governed by admin-configurable daily budget caps, let the organization open access to a much broader employee base, including non-engineers, without the cost or risk of blanket subscriptions.
Project Outcome and Impact
Over the one-month engagement (June 1 to July 1, 2026), the organization expanded AI coding access from 15 engineers to about 45 employees, a 3x increase in the population able to contribute to product development, cutting time to market by at least 30 days.
- Of the 45 with access, roughly 9 were active monthly users, generating 1.6 billion input tokens and 12.9 million output tokens across the 9 models and 4 providers.
- The previous subscription model would have cost $900 per month for the full 45-person population regardless of actual use. Actual monthly spend under CodeVector came in at approximately $130, an 85% reduction, at $14.40 per active user versus $20 under a flat subscription.
Conclusion
This engagement shows what becomes possible when access isn't gated by fixed subscription cost: a team can extend AI tools to a much broader, less technical population and see a direct impact on time to market, while a consumption-based governance model keeps spend proportional to actual use rather than headcount.
Rollouts like this tend to be championed by just one or two individuals within an organization rather than a broad initiative, which is worth keeping in mind when planning who to engage first for a similar expansion.
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