// CONSULTING
Senior AI-infrastructure help, from engineers who've shipped the hard parts.
Start with a scoped discovery sprint. If you need someone to build it, too — we do that.
// THE ENGAGEMENT
Enter low, climb only as far as you need.
Discovery sprintPHASE
Fixed-scope, paid engagement to scope the system: problem, architecture, build path, and what would have to be true for it to work in production.YOU WALK AWAY WITHA real architecture and build plan you own. We'll audit your current system and give an honest read on feasibility, risk, and next steps.
Advisory & architecturePHASE
We take care of the system design and the hard-call decisions. You bring the hard problem, and we bring senior AI-infrastructure judgment.YOU WALK AWAY WITHDeeper system design plans, architectural mock-ups and hard analysis of data structures and storage systems. A clear path forward and a technical project in motion.
Build the MVPPHASE
If you don't have a team to build it, we do. Hands-on delivery of the first real version, built to the architecture from Stage 1.YOU WALK AWAY WITHWe ship a real MVP to production, instrumented and observable, with a clear path to maintainability. You own the code and the architecture.
Managed servicesPHASE
Ongoing support scoped to what you actually need. We figure out next steps together to monitor and achieve defined SLAs.YOU WALK AWAY WITHDetermined together, per your requirements. We can provide on-call support, monitoring, and maintenance of the system we built together.
// SELECTED WORK
Hard things, shipped.
We build agentic systems, retrieval pipelines, and production-grade infrastructure for teams that already have production to protect. Here are a few examples of the work we've done.
Agentic RAGFull agentic retrieval pipeline for a voice-based reflection app. Retrieval, reasoning, and action all happen in a single agent runtime, with every answer traceable to its source.RAGagentsvoice pipelineretrieval
LiteLLM cost routingMulti-provider LLM routing layer with cost controls and model fallbacks. We prioritize keeping inference spend predictable under variable load.LLM routingcost controlinfrastructure
End-to-end encryptionUser-data encryption across storage and transit. We designed permissions so administrators and employees cannot directly read user content.encryptionprivacymobile
Stripe / billingSubscription and payment flows integrated with Stripe — trials, upgrades, webhooks, and entitlement enforcement wired end-to-end.Stripebillingpayments
Compliance workData-handling and access-control patterns aligned to compliance requirements in a regulated context.complianceaccess controldata handling
Qwen3 LoRA fine-tuningTask-specific fine-tuning of open-source models using LoRA adapters.fine-tuningLoRAQwen3
// WHO THIS IS FOR
When to call.
Your AI works in the demo but falls over in productionYou've proven the concept but the production version breaks under real load, real data, or real edge cases. We've seen that failure mode before, and we know how to engineer past it.
You're a founder with no AI team — and you need it builtYou have the vision and the domain knowledge, but you need people who can scope the system and then deliver it. We cover both.
You have engineers but need senior judgment on the hard callYour team is capable but this architecture decision is high-stakes — model selection, retrieval design, infrastructure tradeoffs. Bring in a second opinion before you commit.
Discovery sprint
Start with a discovery sprint.
Fixed scope, real deliverables, and a plan you own — before committing to anything larger.
Tell us what you're
building.
Send the problem, the systems it has to touch, and the deadline. We will tell you what it takes to engineer it, or if it's not a fit we will help guide you to a better solution.