Contextify
Helping teams make sense of internal information with an in-app AI assistant—built and tested as a viable startup
✦ Challenge
Startups often struggle with internal communication, especially across teams with different expertise. Our initial idea was to build a communication assistant that could translate professional jargon and improve cross-disciplinary understanding.
But as we ran our first set of business experiments, a deeper pain point emerged: employees weren’t just confused by terminology—they were overwhelmed by fragmented documentation. Teams were wasting time trying to find, interpret, or simply access the right internal knowledge.
The real problem wasn’t language. It was context.
✦ Approach
Contextify was developed as part of the Innovation Lab course within the SDSI master’s programme. Our five-person team followed a structured startup development process, using tools like the Business Model Canvas and Value Proposition Canvas to formulate and test assumptions. We ran nine business experiments in total, including:
- User interviews to map key jobs, pains, and current coping strategies
- Scenario testing with an early “jargon translator” prototype
- Surveys to validate desired features and information challenges
- Social media discovery posts to spark discussion and gauge resonance
- Expert interviews to refine the pricing and revenue model
- Competitor analysis using SWOT and PESTEL
- A public landing page test to measure interest and traction
A key insight from our initial tests:
Jargon is a short-lived pain—teams learn it. But making sense of scattered documents remains a daily challenge. This triggered a strategic pivot. We redefined our value proposition and redesigned the concept:
Contextify became an in-app AI assistant that helps employees find, summarise, and understand internal company information—wherever they work.
✦ Outcome
The final concept was a high-fidelity prototype of Contextify—a floating desktop assistant that lives inside your workflow. Unlike traditional knowledge bases or AI tools, Contextify integrates directly into platforms like Slack, Outlook, and Notion, allowing you to:
Chat with your data — ask natural language questions and receive relevant answers from across your company’s documentation
Summarise and explain content — turn dense internal reports into digestible insights
Find the right expert — if AI can’t help, Contextify connects you to a subject matter expert
Work without switching apps — the assistant travels with you as a small popup across tools and screens
Through iterative testing, we validated both user interest and business potential:
- 88.9% of survey respondents wanted seamless integration
- 77.8% were interested in querying company data via chat
- Scenario testing showed improved understanding across all participants
- Feedback from our landing page was highly positive, with multiple users expressing willingness to test a live version
We developed a pricing strategy based on market benchmarks, supported by interviews and market size modelling. Our final Business Model Canvas projected a sustainable path from early-stage adoption to long-term growth.
This project taught us the value of experimentation before execution—how starting with assumptions, not solutions, leads to more grounded, desirable outcomes.
✦ Methods & Deliverables
Methods: Business experiments, user interviews, surveys, scenario testing, landing page test, competitor analysis, pricing validation
Deliverables: Updated Business Model Canvas, Value Proposition Canvas, click-through prototype, brand concept, investor pitch materials
Deliverables: Updated Business Model Canvas, Value Proposition Canvas, click-through prototype, brand concept, investor pitch materials