Building an in-house AI team requires significant investment—not just in salaries, but in recruiting time, infrastructure, and ongoing training to keep pace with rapidly evolving technology. For most companies, especially those launching their first AI product or testing a new concept, outsourcing to a specialized partner is faster, more cost-effective, and lower risk.

The right AI development partner brings battle-tested expertise across multiple industries and use cases, eliminating the learning curve that slows internal teams. You get senior-level talent from day one, flexible engagement models, and the ability to scale up or down as your project evolves.

Not sure which path fits your situation? Let’s talk through your goals and find the right approach together.

Off-the-shelf AI tools work well for generic use cases—basic chatbots, standard analytics, simple automation. But when your competitive advantage depends on proprietary data, unique workflows, or differentiated user experiences, custom development is the only path forward.

Custom AI solutions are built around your specific business logic, trained on your data, and designed to integrate seamlessly with your existing systems. The result is a product that does exactly what you need—not a workaround forced into a template built for someone else.

Have a use case that doesn’t fit the mold? We specialize in building AI that’s tailored to your problem.

Timelines vary based on complexity, but here’s a realistic framework: a focused MVP with core AI functionality typically takes 8–12 weeks. A more comprehensive product with multiple models, integrations, and polished UX can take 4–6 months. Enterprise-grade systems with regulatory requirements or large-scale data pipelines may extend beyond that.

The key to staying on schedule is starting with a clear scope, validating assumptions early, and working with a team that’s built AI products before. We use agile sprints with continuous delivery so you see progress every week—not a big reveal at the end.

Ready to map out your timeline? Share your idea and we’ll give you a realistic roadmap.

Cost depends on scope, complexity, and how much existing infrastructure you have in place. A lightweight AI MVP might start around $30,000–$50,000. Mid-complexity products with custom models and integrations typically range from $75,000–$150,000. Large-scale enterprise solutions can go higher depending on data requirements and compliance needs.

What matters more than the number is the return. A well-built AI product can automate manual processes, unlock new revenue streams, or create defensible competitive advantages worth multiples of the initial investment.

Want a ballpark for your specific project? Tell us what you’re building and we’ll give you an honest estimate.