Define the smallest useful result
On the fit call we identify the workflow, deadline, systems, and acceptance test, including the data and brand-safety controls it has to satisfy. You get a direct answer, not a pitch deck.
For e-commerce teams with a deadline and an open AI role
Your e-commerce AI hire may not land before peak season.
Your e-commerce AI hire may not land before peak season.
We can ship the feature while you keep hiring.
Give us one commerce workflow - product-data enrichment, an agentic-commerce feature, ops automation. We define the acceptance test, build it in your environment, and hand an operable system to your team. Technical scoping or a prototype starts at EUR 1,000; production builds are fixed-price after scope.
Check if your feature fits
30 minutes. Leave with a yes, a no, or a tighter scope.
Fixed scopeBuilt in your accountsBuilt in your stackClean handoff
Start with one deliverable, not a large commitment
A technical scope, evaluation setup, integration, or prototype can start at EUR 1,000. If the feature needs a production sprint, you approve a fixed deliverable, price, and acceptance test before work begins.
Watch it work every week
The build runs in your environment. Weekly demos expose progress, tradeoffs, and failures before handoff day.
Own the result
Your team keeps the code, infrastructure, evaluations, audit trail, deployment notes, and recorded walkthroughs. No required retainer.
This is for you if
- You are recruiting a senior AI engineer, but a brand, retailer, or peak-season milestone cannot wait for the search to close.
- A product-data or agent prototype works in a demo but still needs integrations, evaluations, monitoring, and failure handling before real orders touch it.
- Your catalog spans many SKUs or marketplaces and the workflow needs reliable data and guardrails.
- Your team can maintain the feature after launch but cannot absorb the initial delivery work right now.
Not sure the scope is small enough? Book the call. We will recommend a smaller first deliverable or tell you plainly that we are not the right fit.
Meet the builders. Inspect the delivery standard.
We will not manufacture customer quotes. Instead, you can inspect the people leading the work, their public technical writing, and the acceptance criteria used to define a real result.
Dmitri Bogatenkov
AI and systems architecture
Production AI, RAG, evaluation, and HIPAA and SOC 2 workflow architecture.
Sergei Bogatenkov
Product design and delivery
More than a decade in software, plus AI-native interfaces, integrations, and product delivery.
PassAnswers and actions use only approved catalog and policy data
PassHuman approval is required before any customer-facing change
PassEvery run records latency, model cost, and outcome
PassFailure paths return a specific recovery action
Targets are adapted to your workflow and signed off before delivery begins.
What can fit
The best first engagement has one user, one workflow, and one result your team and your auditors can verify.
Good starting points
- Product-data enrichment or catalog cleanup agent
- Agentic-commerce visibility or recommendation feature
- Order, returns, or inventory ops automation
- Catalog search or Q&A with citations and permissions
Usually not a fit
- Replacing your entire storefront in six weeks
- Open-ended "AI transformation" without a user workflow
- Five unrelated features presented as one project
- A build without access to data, systems, or an internal owner
Inside a full production sprint
Smaller starting engagements use only the steps they need. For a six-week production build, the work advances through this sequence with a working demo every week.
Week 1
Scope, data, architecture
Scope sign-off, data access, model selection, integration map, compliance controls, and a working development environment.
Weeks 2-3
Working build and integration
The core workflow runs end to end, then connects to your storefront, catalog, order, and marketing systems.
Weeks 4-5
Evaluation, security, observability
Edge cases, evaluation targets, latency and cost limits, access controls, audit logs, and monitoring.
Week 6
Launch and handoff
Production deployment, documentation, audit trail, recorded walkthrough, and a clean transfer to your team.
Questions we get on the scope call
Can you plug into our storefront and catalog systems?
Yes. The build runs in your accounts and connects to your storefront, catalog, order, and marketing systems, with brand-safety and data controls designed into the feature.
How can you ship a real e-commerce AI feature in six weeks?
We limit the engagement to one bounded workflow, define acceptance criteria before work starts, build in your environment, and demonstrate working software every week. Broader products are split into smaller deliverables instead of forced into an unrealistic deadline.
Do you work inside our data and brand-safety boundaries?
Yes. The build runs in your accounts and environment, with GDPR, PCI where relevant, and data-residency requirements designed into the feature rather than bolted on afterward.
Who specifically leads my sprint?
One of the co-founders, Dmitri or Sergei Bogatenkov, is on every sprint as the technical lead, with a senior engineer working alongside. Dmitri's background is production AI and systems architecture. Review Dmitri's profile or Sergei's profile.
What happens after the sprint?
You own the code, models, infrastructure, deployment, evaluations, and documentation. We can support the handoff or discuss follow-on work separately, with no retainer required.
How much does it cost?
Technical scoping, an evaluation setup, or a prototype can start from EUR 1,000. Larger production builds receive a fixed scope, price, and acceptance test before work begins.
Take one e-commerce feature off the hiring critical path
The 30-minute call ends with a yes, a no, or a smaller recommended scope. Technical starting deliverables begin at EUR 1,000, with no required retainer.
Not in e-commerce? See the main AI Feature Sprint.