New playbook: when your own AI model pays. Read
Ramp (fintech, ~1,200 employees) reported this on 19 Aug 2026 in company self-report (source). It belongs to the models and routing layer.
A routing layer that runs Ramp's production AI traffic across 100+ use cases: one API, shadow-testing candidate models on live traffic, flex-tier routing, benchmark routing, and per-request cost tracing.
Cut Ramp's own LLM costs 30% while improving speed and intelligence, CTO Rahul Sengottuvelu said in July 2026.
The number covers company claims; Ramp has; published the underlying data is not reported.
One gateway picks the AI model for each task and records what it costs.
Up to 90%
lower AI cost, AT&T says
An internal AI Gateway that, turn by turn, weighs speed, cost and expected quality and routes each prompt to the most cost-effective model, switching models mid-session, plus a library of post-trained open telco models (OTel 2.0) that run on-prem or in cloud (source).
<8%
of closed-model cost per transaction
A blended model portfolio (in-house compact models, open-source models post-trained on Pinterest data in its own secure cloud, closed models only in 'very limited cases') behind a centralized routing layer that sends routine work to lighter models; being extended to internal engineering and sales tools in H2 2026 (source).
52%
lower cost per agent session since the June peak
A cost equation and weekly metric stack for its agentic 'software factory' (70%+ of PRs agent-attributed), with benchmark-driven Pareto model selection (incl. open-weight models), cheaper default subagent models, Medium reasoning effort default, 400K-token compaction cap and prompt-cache strategy (source).