Question 1

How quickly can you start my project?

Accepted Answer

We typically deploy core teams within 2 weeks. Our agile process means no long discovery phase or onboarding lag — we move at startup speed with enterprise discipline.

Question 2

Do you work with legacy systems?

Accepted Answer

Absolutely. Legacy modernization is one of our core strengths. We migrate monoliths to secure, cloud-native microservices without taking your business offline while we work.

Question 3

How do you handle data security?

Accepted Answer

Security is built in via DevSecOps — not added at the end. We follow SOC 2 / HIPAA-aligned practices from sprint one, implement zero-trust architecture, and conduct regular penetration testing.

Question 4

Who owns the code and IP?

Accepted Answer

You do. 100%. Once delivered and paid for, all source code, designs, and documentation belong specifically to your company. No licensing gotchas.

Question 5

Do you provide post-launch support?

Accepted Answer

Yes. Flexible SLAs covering 24/7 monitoring, security patching, performance optimization, and ongoing feature work. We don't disappear after go-live.

Question 6

What pricing models do you offer?

Accepted Answer

Fixed Bid for clear scopes (clarity and budget certainty) and Time & Materials for evolving roadmaps (flexibility to adapt). We recommend the model that protects your investment best.

Question 7

Is it really free? What's the catch?

Accepted Answer

No catch. It's a 60-minute working session with a senior AI engineer — no pitch deck, no commitment. We do a handful of these every month because the conversations are how good engagements start. If we're not the right fit, you still leave with a written summary you can use.

Question 8

We don't have an AI strategy yet — is this still useful?

Accepted Answer

Especially then. Most of the value is in deciding what NOT to build. We'll pressure-test the use case, sanity-check ROI, and tell you which 80% of vendor demos to ignore. For a sense of the shape of work that survives that filter, see our AI case studies.

Question 9

Will you look at our actual stack and data?

Accepted Answer

Yes — bring whatever you can share. Architecture diagrams, prompts, eval traces, retrieval setup, model bills, anonymized samples. The audit gets sharper the more concrete it is. Anything you share stays under NDA and is yours.

Question 10

Who shows up on the call?

Accepted Answer

A senior AI engineer who has shipped production GenAI / agent systems — not an account manager. Depending on your stack we may bring a second specialist (data, MLOps, or platform) so you get a real second opinion, not a sales hand-off.

Question 11

What do I walk away with?

Accepted Answer

A short written summary covering: the highest-leverage problems we'd tackle first, the architecture choices we'd defend or change, specific risks (cost, latency, hallucination, eval, guardrails), and a rough sequencing. You can share it internally as-is.

Question 12

How is this different from a generic 'discovery call'?

Accepted Answer

Discovery calls are about us learning your budget. This is about you getting a useful technical opinion. We come prepared, we go deep on one or two problems instead of skimming ten, and we're explicit about what we don't know.

Essays from the people who ship.

Digital Transformation

AI & Data Science

Product Engineering

Data Analytics

Experience Design

Quality Engineering