Honestly? It depends on complexity. We usually get a working pilot in front of you within 4-8 weeks. Enterprise-grade systems with custom models take 3-6 months. We work in sprints so you see progress early—not months of silence followed by a big reveal.

You do. 100%. All code, all trained models, all documentation. We hand it over under your license. No vendor lock-in, no strings attached.

We take security seriously—threat modeling, least-privilege access, encryption everywhere, audit trails. We can work on-premises, in your cloud, or in isolated environments. GDPR, HIPAA, SOC 2 frameworks? We've navigated all of them.

A focused AI MVP starts around $25K-50K for 4-8 weeks. Enterprise solutions can run $100K-500K+. We'd rather give you a real number than a vague range—that's what the discovery call is for.

Absolutely. We offer SLA-based maintenance, 24/7 monitoring, model retraining, and continuous improvement. Some clients need basic bug fixes; others want us as an extension of their team. We're flexible.

Python is our bread and butter for AI—TensorFlow, PyTorch, LangChain, OpenAI APIs. For full-stack, we use React, Next.js, Node.js, FastAPI. Cloud-wise: AWS, GCP, Azure. We pick what fits your needs, not what's trendy.

That's actually what we do best. Legacy systems, modern cloud apps, IoT devices—we design APIs and microservices that slide in without breaking what's working. REST, GraphQL, webhooks, message queues, direct database connections. Whatever you've got.

Healthcare (medical imaging), finance (fraud detection), retail (recommendations), manufacturing (quality control), hospitality, fitness, jewelry—honestly, we've been around. We adapt quickly because we've seen enough patterns across domains.

We've done it all: cameras, sensors, PLCs, custom hardware. We optimize models for edge (TensorFlow Lite, ONNX), handle real-time telemetry, and build offline-first architectures. If it has a sensor and needs to be smart, we can work with it.

Free 30-minute call first—we want to understand what you're trying to solve. Then a 1-2 week discovery phase to assess your data and define success metrics. After that, 2-week sprints with regular demos. You'll see something working fast.

Yes—feasibility assessments, data strategy, ROI analysis, roadmap planning, team training. Sometimes you just need someone to tell you honestly whether an AI project makes sense before you commit.