Internal AI Tools
Build AI-powered internal tools that your team actually uses — without justifying a dedicated GPU budget to finance. Lexora's pay-per-use model is perfect for bursty, internal workloads.
Why internal tools are perfect for serverless inference
Internal tools have the most bursty usage patterns imaginable: heavy during business hours, completely idle nights and weekends. A dedicated GPU running 24/7 for a team of 20 that uses the tool for 6 hours a day would sit idle 75% of the time. Serverless inference charges for those 6 hours, not the full 24.
No approval needed for dedicated GPU budget
Start with $1 of free credit. Scale usage as adoption grows within the team. No upfront commitment.
Works during business hours, free at night
Serverless infrastructure costs $0 at 2am when nobody's using it. A dedicated GPU would still be billing.
Easy to shut down if unused
No infrastructure to decommission. If the tool isn't used, you pay nothing. No stranded capacity.
Same API as OpenAI for easy prototyping
Build and test with the OpenAI SDK, then point to Lexora's endpoint for production deployment.
Internal tools you can build
Real cost example
A team of 20 using an internal document summarizer 10 times each per day:
- →200 requests/day × ~2,000 tokens each = 400K tokens/day
- →400K × 30 days = 12M tokens/month
- →12M tokens × $0.04/1M = $0.48/month
- →vs. dedicated A10G GPU: ~$540/month
Result: $0.48 vs $540 — a 1,125× cost difference.