Questions, answered

Most start with a short scoping conversation where we figure out what you're actually trying to build and where the real risk sits. From there we agree on a first slice of work with a clear outcome and timeline, so you see something working before committing to anything large. No long discovery phase that bills for months and ships nothing.

Both, depending on what fits the work. Well-defined builds with a clear spec usually work best as fixed-fee with named milestones. Ongoing platform work, where priorities shift week to week, tends to run as a monthly retainer for a set amount of capacity. We'll tell you which one makes sense for your situation rather than pushing the one that pays us more.

Pricing follows the engagement model. Fixed-fee work is quoted per milestone against an agreed scope, so you know the number before we start. Retainers are a flat monthly rate for a committed level of senior engineering time. There are no per-seat license fees and no markup on cloud or third-party costs, which you pay directly.

A focused build that proves out an idea usually lands in four to eight weeks. A production platform with real data, integrations, and operational hardening is more often a few months. We size the first slice deliberately small so you get working software early and can judge the pace yourself before we go further.

You do. All work product, source code, and related intellectual property transfer to you as it's delivered and paid for. We don't keep hooks, hidden dependencies, or licensing that ties you to us. Everything lives in your repositories and your cloud accounts from day one.

We plug into how your team already works rather than running a separate track. That means your repositories, your code review, your standups and planning, and shared ownership of decisions. We're happy to lead, pair, or quietly fill gaps depending on what your team needs, and we leave behind documentation and people who understand the system.

Launch is a milestone, not an exit. We can stay on for a defined support window to handle the issues that only show up under real traffic, then taper to a lighter retainer or hand off entirely. Either way we make sure your team can run, debug, and extend what we built, with runbooks and a clean handover rather than a dependency on us.

We treat model output as something to be constrained, not trusted by default. That means grounding responses in your own data, keeping clear retrieval and citation paths so answers can be traced back to a source, and adding guardrails and evaluation so behaviour is measured rather than assumed. For anything customer-facing, we build in human review and fallback paths for the cases the model gets wrong.

Yes. We've built systems where data residency, audit trails, access controls, and approval workflows are requirements, not afterthoughts. We work inside your compliance constraints, document decisions for auditors, and design data flows so sensitive information stays where it's allowed to be. If you have a specific framework you answer to, we design to it from the start.

We're pragmatic about tools and pick what fits the problem and your team's ability to maintain it. In practice that's mostly TypeScript and Python, Postgres and the usual cloud data services, and the major cloud providers for infrastructure. We won't introduce something exotic just because it's interesting if a boring, well-understood choice will serve you better for years.