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Academic consulting project

AI Startup — Strategic Market Consulting

An academic consulting engagement for an early-stage AI company developing automated image-processing and synthetic-data solutions. The project evaluated potential industry verticals and developed a focused market-prioritisation and go-to-market recommendation.

Market PrioritisationStrategic PositioningGo-to-Market Strategy
Project TypeAcademic consulting project
MethodsMarket research, benchmarking, prioritisation
FocusVertical selection and differentiation
DeliverableStrategic recommendation + roadmap

Business Challenge

The startup operated in a highly competitive AI infrastructure market where broad technical capability did not automatically create a defensible market position. The central challenge was to identify a vertical where customer pain, market attractiveness, adoption readiness, regulatory conditions, and implementation feasibility could support stronger differentiation.

Which market vertical should the company prioritise to achieve stronger differentiation and scalable growth?

Strategic Decision Framework

The team compared potential applications through one structured decision framework rather than selecting a market based only on headline size.

7-Criterion Evaluation Scheme
01
Market attractiveness
02
Demand potential
03
Competitive intensity
04
Regulatory environment
05
Adoption barriers
06
Implementation feasibility
07
Scalability and defensibility

Research & Analysis

Market and vertical research

We researched multiple potential applications and compared the commercial logic of each vertical, including customer pain, demand maturity, market structure, and the role synthetic data could play.

Competitive benchmarking

We assessed direct competitors, adjacent solutions, positioning gaps, and the degree to which vertical specialisation could create a clearer value proposition.

Feasibility and adoption

We considered regulation, data access, technical integration, adoption readiness, implementation complexity, and the risks associated with entering each market.

Recommendation Logic Pipeline

5-Step Strategic Pipeline Scheme
01
Customer Pain
Start with a clearly defined, high-urgency customer problem.
02
Tech Role
Ensure synthetic data plays a relevant, core technological role.
03
Business Value
Demonstrate clear, quantifiable economic value for adopters.
04
Adoption Reality
Validate realistic compliance, data access, and integration friction.
05
Defensible Differentiation
Establish a specialized, defensible barrier against horizontal players.
Strategic Recommendation

Shift from broad horizontal competition to focused vertical specialisation.

  • Prioritise a clearer, high-value vertical use case
  • Align tech capabilities with market demand and adoption reality
  • Reduce go-to-market ambiguity through focused positioning
  • Strengthen long-term competitive differentiation
  • Support scalable, repeatable market entry

Go-to-Market Roadmap

Stage 1

Validation

Validate customer pain, use cases, technical requirements, and buying logic.

Stage 2

Pilot Design

Define a focused pilot, success criteria, and technical and commercial validation requirements.

Stage 3

Focused Market Entry

Refine positioning, target segments, messaging, and initial customer-acquisition priorities.

Stage 4

Expansion

Scale after evidence of product–market fit and repeatable implementation.

My Contribution

Independently Developed / Led

  • TAM / SAM / SOM market sizing and prioritization logic
  • Positioning-gap analysis vs direct and adjacent competitors
  • Structuring the final executive analytical storyline
  • Presenting and defending the strategic recommendation directly to the CEO

Contributed To

  • Market and vertical background research
  • Competitor benchmarking across candidate industries
  • Demand, regulation, and implementation friction comparison
  • Roadmap and KPI framework development

Outcome & Deliverables

The final analysis and recommendation were presented directly to the CEO. During the Q&A, the team defended the evidence, trade-offs, assumptions, implementation risks, and feasibility of the proposed direction.

The project delivered a validated strategic direction and an actionable roadmap. It did not include measured post-launch commercial results.