The form has been successfully submitted.
Please find further information in your mailbox.
Hire usSelect language
About us
TechnologiesIndustriesPortfolio
We provide an in-depth exploration of your AI concept or AI readiness assessment to set measurable outcomes and identify technical, ethical, financial, and other risks.
Based on your goals, we define a step-by-step AI implementation plan with key milestones and resources. Our roadmaps delineate task priorities and dependencies, keeping all in the loop.
Our team develops a “sandbox” solution to test concept feasibility and expected value. Check it with real users or systems before a full-fledged investment.
Finally, we perform all steps critical for making your AI-based system rock-solid and ready for scale, including performance optimization, infrastructure setup, and monitoring.
What we noted during the workshop was the experience that Innowise as a company and their team member as an individual had, with a good answer for every real-life and hypothetical scenario we could think of.
Prior to starting our engagement, we had reviewed several IT companies on the market, and none compared to Innowise in terms of cost of service and the calibre of software developers that worked with us on the project.
Innowise’s collaborative ethos, technical prowess, and unwavering commitment to our success have left a lasting impression on us. Their ability to seamlessly integrate with our internal teams and adapt to the ever-evolving demands of our projects exemplifies a true partnership.
Look for an AI consulting company with a great AI implementation portfolio. They should demonstrate what works in practice and possess a track record of matching dozens of unique business challenges with reliable practical execution. It’s important that they’ve worked in your industry, understanding specific regulations and constraints.
AI consulting costs can vary based on the scope of your project. Basic projects might start at a few thousand dollars, while complex long-term engagements could go into the tens of thousands or higher. Better think of it as an investment that can deliver substantial returns with robust foundations.
Ask questions that dig into their practical experience and approach. First, ask them to share a past case study where a similar problem was solved. Then, find out how they ensure AI models stay relevant as data changes and how success is measured after deployment. Check their communication approach to avoid misalignment between goals and outcomes.
Reducing risk starts with alignment on goals and an understanding of AI limitations. A step-by-step process allows for frequent testing and iteration to validate assumptions. Regular audits, clear documentation, and ongoing model monitoring are key to catching issues early. It’s also essential to set up ethical safeguards to avoid unintended bias or unfair outcomes.
AI consulting is valuable when aligning business goals with execution, defining PoC objectives, and tackling complex or innovative problems. The more challenging the problem, the more critical consulting becomes. For well-defined problems, you may proceed directly to discovery or prototyping without full consulting support.
It depends on the complexity of your idea and the resources at hand. Typically, an AI Proof of Concept (POC) takes about 4-6 weeks, focused on demonstrating feasibility. An MVP (Minimum Viable Product) takes longer, typically 2-3 months, to develop a working prototype that can be tested with real users.
We leverage a robust deployment framework that includes scalability, security, and monitoring. Compliance comes from building models with data privacy in mind and ensuring they meet industry-specific regulations, e.g, GDPR or HIPAA. We have ongoing validation checks, ensure traceability of decisions, and maintain a system for model updates and audits.
