Which industries do you work with? +
We've shipped in healthcare, fintech, retail, logistics, SaaS, energy, legal, media, and enterprise operations. The common thread is repetitive workflows or complex knowledge that an AI system can take off your team's plate.
Do you work with startups or only enterprises? +
Both. We run fixed-scope sprints for startups and monthly engineering pods for enterprises. The case studies here span pre-seed companies through Fortune 500 operators.
How much does a project like these cost? +
Cost depends on scope, integrations, data preparation, and security requirements. Prototypes typically start in the low tens of thousands; enterprise rollouts are quoted after a scoping sprint so there are no surprises.
Who owns the code and models you build? +
You do. Full IP transfer on delivery — code, prompts, model weights where applicable, and documentation. We keep nothing you didn't agree to share.
Do you integrate with our existing systems? +
Yes. We integrate with CRMs, ERPs, data warehouses, ticketing, communication tools, and custom internal applications via their APIs, respecting your existing permissions and access controls.
How do you handle data security and compliance? +
We design with access controls, encryption, audit logging, and approval workflows from day one, and align with requirements like SOC 2, HIPAA, and GDPR depending on your industry.
What AI models do you use? +
We're model-agnostic — Anthropic Claude, OpenAI, Google Gemini, and open-weight models — and choose based on accuracy, cost, latency, and privacy needs so you're never locked into one provider.
Do you keep a human in the loop? +
For sensitive or high-risk actions, yes. Low-risk tasks can run autonomously, while critical workflows route through human approval, escalation, or review before anything is finalized.
What happens after launch? +
We monitor performance, gather user feedback, tune prompts and retrieval, and add integrations over time. Most systems improve significantly in the months after go-live.
How do you scope a new engagement? +
Every project opens with a fixed-scope scoping sprint: we map the workflow, data sources, users, and systems, define success metrics, and produce a clear plan and estimate before any build work begins.
What team will we work with? +
You work directly with the senior engineers building your product — no account-manager layer. Pods are typically 2–5 engineers paired with AI tooling, with a lead who owns delivery.
How do you report progress during a build? +
We demo working software weekly so you see real progress, not status slides, and you have direct access to the team in a shared channel throughout the engagement.
What if the results don't match the projection? +
Because we instrument metrics from the start, we catch underperformance early and iterate — tuning models, data, and workflows. Scoping sprints are designed to de-risk this before the main build.
Can you build internal tools, not just customer-facing ones? +
Yes. Many of these case studies are internal — finance automation, HR self-service, ops copilots, knowledge search — built for employees rather than end customers.
Do you offer ongoing support and maintenance? +
Yes. After delivery we offer support and optimization retainers covering monitoring, evaluation, model updates, and new feature work as your needs evolve.
How do we get started? +
Book a free 30-minute consultation or start a project brief. We'll review your goals, suggest the right engagement model, and outline next steps — usually within 24 hours.
