Spend management
Meter AI usage and cost, define layered access, and enforce budgets across models and workloads so spending stays controlled.
Corporate AI
We help companies control AI costs, evaluate performance, and improve accuracy. We ground systems in trusted company knowledge so adoption is practical and measurable.
How we help
Evaluations
Build repeatable evaluations that measure accuracy, reliability, and business fit before and after deployment.
Knowledge bases
Ground AI systems in trusted company knowledge so answers are accurate, relevant, and current.
Selected work
-
SituationA hedge fund needed an LLM to interpret time-series model outputs alongside current data and news. General-purpose models relied on static model weights, while tool-based web browsing was too slow for the workflow.
Our workWe built the full post-training pipeline: context engineering, RAG scaffolds, supervised fine-tuning, low-latency inference streams, LLM graders, and evaluation pipelines. The system combined time-series outputs with up-to-date market data and news and was deployed in a pilot.
-
SituationA criminal defence practice wanted to apply general-purpose AI to legal research and document preparation while protecting privileged and sensitive client information. The practice needed a practical starting point rather than a broad transformation program.
Our workWe delivered a practice-specific adoption advisory covering privacy and data controls, tool selection, bounded access to files and email, web-assisted legal research, and reusable structured prompts and task-specific workflows. The guidance prioritized confidentiality, controlled experimentation, and clear judgment about where AI should—and should not—enter the work.
-
SituationCircuit Skipper needed to provide free and paid access to multiple AI capabilities without allowing variable model costs to outrun the economics of each subscription tier.
Our workWe implemented backend-authoritative subscription entitlements, capability-specific paywalls, free-tier request limits, and dollar-denominated monthly AI caps for Pro. Online AI use is metered against the applicable limit, while atomic quota enforcement and real-time cost calibration keep access predictable and model spend bounded.
-
SituationSaltwater Games needed NPCs that could respond to players based on live game state, alongside faster proof-of-concept asset generation inside its Unity development environments.
Our workWe implemented AI-enabled NPC dialogue using AWS, Anthropic, and OpenAI infrastructure. The agents decided what to say based on game state, including player achievements and inventory. We also integrated a Leonardo AI widget across the company’s Unity deployments for in-workflow asset generation. Both systems were adopted and used in production.
Start a conversation