Guided exploration by Supertype experts
Opportunity Discovery
Analytics and automation infrastructure for the AI era does not need to feel daunting or black-boxed. We put our most qualified AI engineers to work, guiding you through a hands-on discovery process to identify the quick wins and continually develop your opportunity radar.
From raw data to fully automated analytics
In under 24 hours, and under $3,900.
We get you results on day one.
Discovery
5 - 7 hours
We start by immersing ourselves in your business and your current processes. This involves one or more sprint sessions and executive-level workshops to understand your largest cost centres, biggest pain points, and most pressing needs.
Business Value Catalog
3 hours
In this phase, we analyze the data collected during the discovery phase to identify patterns, trends, and insights. Our team will work with you to rank each opportunity based on its potential business value and feasibility. This will help us prioritize AI and automation initiatives with the greatest impact.
V1 Engineering
12 - 15 hours
Our AI engineers, analytics developers and data scientists work with you to develop proof-of-concept solutions for the top-ranked opportunities, providing a solid foundation on which your team can build upon.
Continuous Upskilling
Ongoing
Digital transformation is an ongoing process, and we are committed to helping our clients stay ahead of the curve. Post-implementation, we want to continue upskilling your team through specifically tailored consultations and workshops, creating a culture of curiosity and fine-tuning your opportunities radar.
Opportunity Discovery Process
Discovery
•Business Value Catalog
•V1 Engineering
•Continuous Upskilling
Discovery
Guided On-site Exploration and Brainstorming
A 6 to 8 hour workshop hosted in your office or a preferred location. Conducted by our most qualified AI engineers with demonstrated experience in your industry.
- Case Study Focused: Learn what works for industry peers
- Suitable for C-Levels and Executives
- Practical, Targeted Outcomes
Business Value Catalog
Goal-oriented approach to AI implementations
Weighing the business value of each initiatives against the cost of implementation, we help you hone in on the low-hanging fruit and win internal buy-in quickly through a clear roadmap.
- Sourcing ideas from Executives and Employees
- Assigning cost and business value through a structured framework
- Pick the right initiatives for proof of concept and pilot projects
V1 Engineering
Rapid prototyping and AI Proof of Concepts
Within 2 weeks, we can deliver a version 1 prototype of your initiatives, implemented with production-ready code and documentation. AI and analytics systems move fast, so we intend to ship and iterate quickly to deliver value in the shortest time possible.
- No mockups or wireframes. Build and validate in 15 hours of product engineering.
- Ship your POC to gather actual usage data and feedback
- Gain internal buy-in and rally support for your initiatives
Continuous Upskilling
Develop internal AI capabilities and sensitivity
Opportunities in generative AI and agentic automations are abundant, as long as the eyes are alerted to these possibilities. Post-Discovery, we want to continue sharpening the opportunistic radar of your team, so they can identify the quick wins presented by AI and analytics systems along the way.
- Regular check-ins and private workshops
- Tailored resources and digital case studies
- Ongoing mentorship and support
Schedule a Meeting
Resources from Supertype
Print and digital publications on Enterprise AI, including e-books and whitepapers from Supertype's team of experts. These are print-friendly and can be downloaded for offline reading. Latest publications include:
- Agentic Patterns
- Building Search Engines in the Age of AI
Supertype Notes is a collection of field notes, technical essays and article series on enterprise analytics, machine learning, and data science. We welcome contributions from practitioners working on real-world analytics and AI systems.
Featuring field notes that cover a diverse range of topics including data engineering, cloud infrastructure, machine learning and enterprise analytics.
