Project timelines vary significantly based on scope. An MVP typically takes 8–16 weeks. A mid-size enterprise application takes 4–8 months. Larger platform builds can run 9–18 months. We work in two-week sprints and provide detailed timelines during the discovery phase.

Yes, absolutely. We sign mutual NDAs before any detailed project discussions. Confidentiality is fundamental to how we work. Just let us know in your initial inquiry and we'll send an NDA before any discovery sessions.

Discovery is a 1–2 week structured process where we conduct stakeholder interviews, review existing systems, map current processes, define success metrics, and produce a detailed technical specification and project plan. This ensures alignment before any development begins.

All code, designs, and deliverables created during your project are your IP. We include clear IP assignment clauses in all contracts. We do not retain ownership of anything created for your project.

Yes. We frequently get engaged to rescue troubled projects, conduct technical audits, or supplement existing teams. We'll do a thorough codebase and process review before committing so we can give you an honest assessment.

We offer fixed-price contracts for well-defined projects and time-and-materials for evolving engagements. Most projects start with a fixed-price discovery phase, then move to one of these models. We're transparent about rates and never have hidden fees.

There is no minimum project size. We can handle projects of any size, from small tasks to large-scale enterprise applications.

Yes. Many of our clients move to a monthly retainer after project delivery for ongoing feature development, maintenance, and technical advisory. Retainers start priced based on dedicated hours.

Typically net-30 invoicing on a monthly basis for ongoing work, or milestone-based payments for fixed-price projects. We accept wire transfer, ACH, and major credit cards.

Our core strengths are TypeScript/React/Node.js, Python (Django, FastAPI), cloud-native AWS/GCP/Azure, mobile (React Native, Flutter), and AI/ML (LangChain, OpenAI, Hugging Face, vector databases). We're polyglots — we use the right tool for the job.

Absolutely. Staff augmentation and co-development are common engagement models. We integrate cleanly with your existing workflows, tooling, and processes. We're also happy to mentor your engineers as part of the engagement.

We provision all infrastructure as code (Terraform, Pulumi), set up CI/CD pipelines (GitHub Actions, GitLab CI), configure observability (Datadog, Grafana, PagerDuty), and document everything. We typically target 99.9%+ uptime SLAs.

Our AI Practice offers: RAG (Retrieval Augmented Generation) systems, LLM fine-tuning and deployment, AI agent development, workflow automation, computer vision, NLP pipelines, predictive analytics, and AI strategy consulting.

Our clients typically see positive ROI within 6–10 weeks of deployment. We design automation systems with measurable KPIs from day one, so you'll have clear before/after metrics by the end of the first sprint.

We work across the major providers — OpenAI GPT-4o, Anthropic Claude 3.5, Google Gemini 1.5, and open-source models (Llama 3, Mistral, DeepSeek). Model selection is driven by your specific accuracy, latency, cost, and data privacy requirements.

We design for data minimization by default. For sensitive industries (healthcare, finance, legal), we can deploy entirely on-premise using open-source models with no data leaving your infrastructure. We also work with privacy-preserving techniques like differential privacy and federated learning.