How long does an AI MVP usually take?

Most LLM-based MVPs land in 4–8 weeks. Computer vision or model-training projects typically run 8–14 weeks depending on data readiness. We commit to a delivery date after the 1-week discovery phase — and we hit it on 97% of projects.

Do we own the model and the code?

Yes — 100%. All source code, fine-tuned model weights, prompts, ML Ops infrastructure and documentation are transferred to you at delivery. We sign IP-assignment clauses upfront in the MSA.

Can the AI run inside our VPC / on-prem?

Absolutely. We routinely deploy on AWS, Azure and GCP private VPCs. For clients with strict data-residency or air-gap needs we support fully on-prem deployments using open-source models.

How do you handle hallucinations and accuracy?

Every project gets an evals harness: a golden dataset, automated regression tests on every model/prompt change, and production drift detection with alerting. We don’t release an LLM feature without measured accuracy on your data.

Which foundation model should we use?

It depends on the use case. We benchmark GPT-4, Claude, Gemini and open-source models against your task during the audit. Sometimes a smaller open-source model beats a frontier model at a fraction of the cost.

How do you ensure data privacy & compliance?

We’re ISO 27001 certified. We sign DPAs and BAAs upfront. We support HIPAA, GDPR, PCI-DSS and regional data-residency requirements.

What happens after launch?

Every Fixed Scope project includes a 3-month post-launch warranty. After that, optional support packages range from business hours to 24×7 SLA-backed. Most clients move to a Dedicated Team for ongoing iteration.

Can you work with our existing engineering team?

Yes. Staff Augmentation and Dedicated Team models are designed for it. Our engineers join your Slack, Jira and GitHub, pair-program with your team and hand off cleanly.

Transparent rates · 14-day onboarding

Hire calculator — what would a dedicated team actually cost?

Tell us the roles you need, seniority, and timezone overlap — we will send you a monthly rate-card and a 4-week onboarding plan.

Talk to an expert

How it works

Real rates, real onboarding plan.

Pick the roles

Frontend, backend, mobile, AI, DevOps, QA, design, PM — name what you need.

Pick the seniority

Mid (4–6 years), Senior (7–10 years), Staff (10+) — different rate tiers.

Pick timezone overlap

How many overlap hours do you need with your day? More overlap = small premium.

Get the rate card

Monthly retainer in USD per engineer + total team cost.

4-week onboarding

You see exactly how onboarding works: shadow week, NDA, MSA, kickoff, first PR.

NDA & MSA included

No surprise legal — our templates are battle-tested across 200+ engagements.

Tech Stack

Stack we use

Monthly retainer Role-based rate cards Mid / Senior / Staff tiers Replacement guarantee 5-day trial window

FAQs