Meet the teams running inference at scale
Explore how Doubleword customers cut token spend, move non-urgent workloads out of real time, and run reliable batch and async inference without operational overhead.
Case study · NXL
How NXL cut generation costs 79% with no drop in quality using Doubleword
NXL builds AI assistants that handle content, prospecting and coaching for enterprise sales teams.
79%
lower cost per message vs Claude Sonnet
Case study · Ken AI
How Ken AI eliminated inference bottlenecks and cut batch runtimes by 68% with Doubleword
Ken AI is a cold-email agency that runs personalized outbound for B2B SaaS companies on proprietary email infrastructure built in-house.
68%
faster batch runs
Case study · UnaGo AI
How UnaGo AI cut inference costs 70% with Doubleword
UnaGo AI is an AI-native operations platform that gives companies a team of specialist AI agents - marketing, media, research, and operations - working together in a single conversation.
70%
lower inference cost vs. Claude
Case study · OpenMed × SynthVision
119,000 medical images annotated for $452 with Doubleword
How OpenMed used Doubleword to make frontier-model knowledge distillation viable at dataset scale - at 94% lower cost than Claude Sonnet.
94%
cost savings vs. Anthropic
Case study · Dataiku
A custom PII detection model trained for $50 with Doubleword
How Dataiku's 575 Lab used Doubleword to generate the synthetic training data behind Kiji Privacy Proxy - 20× cheaper than closed-source providers.
95%
cost reduction