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.

TOGAF · Cloud · Enterprise

Solution architects — designs that survive the second year.

TOGAF-trained solution architects who design enterprise systems for scale, security, and maintainability. From green-field to legacy modernization.

Talk to an expert

What we provide

Architecture deliverables that engineering teams can ship from.

Reference architectures

Documented architecture with diagrams, ADRs, and trade-off analysis.

Cloud architecture

AWS / Azure / GCP landing zones with Well-Architected Framework compliance.

Modernization

Strangler-fig migrations off monoliths and legacy databases — incremental and safe.

Security & compliance

, HIPAA, GDPR, ISO 27001 — architecture that audits well.

Architecture review board

Embedded architects who attend your design reviews and unblock decisions.

TOGAF & C4

Enterprise architecture with TOGAF / C4 model documentation everyone can read.

Tech Stack

Stack we use

TOGAF C4 Model AWS Well-Architected Azure CAF Domain-Driven Design Event Storming Confluence Lucidchart Structurizr

FAQs