1. SAMENVATTING (Summary)

Huddly AI helps small business owners in Zuid-Nederland prepare for succession by digitizing their operations and providing AI-powered guidance—so they don’t close down due to lack of preparation. It is a digital platform designed to help small and medium-sized business owners prepare for succession and exit by digitizing their knowledge, documentation, and operational processes. Most SME owners in the Netherlands and Europe lack the tools, experience, and support needed to sell their business successfully—resulting in missed transitions, business closures, and job losses. Huddly AI addresses this gap with a seller-first, AI-driven solution that makes the complex process of business succession understandable, structured, and achievable.

Developed by Moving Data Insights B.V., a startup based in Eindhoven, the platform integrates:

• A conversational AI assistant that provides personalized guidance via text or voice
• A dynamic workflow engine that adapts to the user’s business context
• A readiness scoring algorithm that evaluates succession preparedness across finance, operations, legal, and continuity domains

The project is being carried out as a feasibility study to validate whether this platform can meet real user needs, function technically at scale, and support a sustainable business model. Key research questions will assess user adoption, pricing, digital literacy, and the trustworthiness of AI-generated readiness scores.

Huddly AI directly contributes to KIA 8 (Maatschappelijk Verdienvermogen) and KIA 7 (Digitalisering) by supporting inclusive economic continuity for SMEs and leveraging AI for practical, user-centric applications. All project activities will be conducted in Zuid-Nederland, leveraging the technical talent of TU/e and the entrepreneurial ecosystem of The Gate.

As a bootstrapped startup, Moving Data Insights requires public co-funding to de-risk development and validate the platform before making further investments. Without this support, the company would be forced to build a minimal version without user validation—undermining the innovation’s potential impact.

This feasibility study enables a research-driven, responsible approach to building a digital solution that helps preserve SME legacies, support local employment, and unlock generational value.

2. PROJECTAANLEIDING EN -DEFINITIE (Background & Project Definition)

We want to validate the feasibility and technical foundation of Huddly AI, a platform that helps SME owners prepare for succession and exit by digitizing their business knowledge and documentation, so that we can test its value with real users and determine its technical and market viability.

2.1 Bedrijfsinformatie (About the Company)

The project is being developed by Moving Data Insights B.V., a startup based in Eindhoven, Zuid-Nederland (KvK: 93868340). The company specializes in AI and data-driven innovation, with a focus on process automation, digital workflows, and user-centric platform development.

The team currently consists of the co-founding CTO—who will lead all R&D activities related to software development and AI implementation—and supporting freelance developers to be sourced from Eindhoven University of Technology (TU/e). The company has strong ties to the local innovation ecosystem, including partnerships with The Gate (a startup hub in Eindhoven) and TU/e itself.

The company’s competencies include:

• Data-driven software engineering
• Conversational AI (LLM integration)
• Digital product development
• Agile project delivery

Website: www.movingdatainsights.com

2.2 Aanleiding en Relevantie (Motivation & Societal Relevance)

Each year, tens of thousands of small business owners in the Netherlands—and hundreds of thousands across Europe—face the need to exit their business due to age, retirement, or life circumstances. Yet, many of these businesses close down not for lack of value, but due to a lack of preparation.

Most owners remain unprepared for succession, lacking clear plans or access to buyers.

This challenge is especially urgent in Zuid-Nederland. In Limburg, 65% of SMEs are family-owned; in Zeeland, that figure exceeds 70%. These businesses form the economic backbone of the region. Many are led by aging owners—more than half are over 55—and face a wave of retirements in the next decade. In Kerkrade, for example, 30% of local family firms must transition ownership in the coming years.

The economic risk is substantial: Family-owned SMEs account for ~2.2 million jobs nationally, with ~7% of all Dutch jobs exposed to succession risk. In Zuid-Nederland—where SME employment concentration is high—thousands of jobs and millions in regional GDP are at stake. Failed handovers already eliminate ~2% of all jobs annually.

Local governments and networks recognize this risk. Programs like TOF Limburg, Kerkrade’s succession pilot, and the Community Zeeuwse Familiebedrijven have emerged to support handovers—but many owners still lack digital, accessible tools to take action.

Huddly AI was born out of this gap.

We help owners understand what’s needed and take tangible steps toward a successful transition.

This project directly contributes to Zuid-Nederland’s regional resilience and aligns with national innovation agendas (KIA 8 & KIA 7).

2.3 Doelstelling (Objective)

The objective of this project is to validate the technical feasibility and market desirability of Huddly AI—a digital platform that helps SME owners in Zuid-Nederland prepare for succession and exit by digitizing their knowledge, documents, and operational processes.

This will be achieved through:

• Development of an AI-supported onboarding experience and dynamic workflow engine
• Research into key bottlenecks and behaviors of SME owners
• Validation of the platform’s pricing, usability, and readiness scoring logic

By the end of the project, the team aims to have tested a functional MVP with real users, evaluated critical assumptions (e.g. digital literacy, willingness to pay), and determined whether Huddly AI can be scaled as a viable innovation to support regional economic continuity.

3. INNOVATIE (Innovation)

Huddly AI is an AI-powered digital assistant that helps small and medium-sized business owners prepare for succession and exit. Its core innovation lies in combining conversational AI, algorithmic readiness scoring, and context-aware workflows to transform an overwhelming, unstructured process into an accessible and guided digital journey.

This platform targets SME owners who have never sold a business before and often don’t know where to start. It helps them identify, complete, and organize the documentation needed for a sale—financial, legal, operational, and continuity-related—while also generating key artifacts (like SOPs and onboarding plans) that make their business more attractive and transferable.

The goal is to make succession accessible, non-intimidating, and practically achievable for SMEs—most of whom currently lack the tools, knowledge, or support systems to exit successfully.

3.1 Beschrijving van de Innovatie:

The core innovation of this project is a modular, intelligent digital platform composed of four tightly integrated components:

1. Conversational AI Assistant:
   Large Language Model (LLM)-based assistant, accessible via chat or voice, that guides business owners step-by-step through the succession planning process. This assistant adapts to the user’s context—business type, industry, document readiness—and helps collect and improve required materials.
2. Dynamic Workflow Engine:
   A logic engine that determines what artifacts (e.g. financial reports, legal documents, internal SOPs) are required, based on user inputs. It creates a personalized roadmap that updates dynamically as the user progresses, giving structure to an otherwise vague process.
3. Readiness Scoring Algorithm:
   A scoring system that evaluates the completeness and quality of the user’s materials across four pillars: Finance, Operations, Legal, and Continuity. It provides feedback to the owner and insight to potential buyers, acting as a progress bar and a trust signal. The AI assistant uses a tag-based metadata system to understand context (e.g. “financial upload incomplete,” “missing succession artifact”), allowing it to proactively recommend next steps based on the user’s progress and known workflow logic.
4. Automated Generation of Business Continuity Documents:
   Huddly AI assists in creating essential handover assets—such as Standard Operating Procedures (SOPs), onboarding instructions, and continuity plans—that enhance a company’s transferability and reduce deal friction. These materials are automatically drafted using AI based on user inputs and uploaded data, helping owners document their business in a structured, buyer-ready format.

Together, these components create an adaptive, AI-supported platform that equips SME owners to confidently prepare, document, and hand over their business in a structured and buyer-ready format. These components will be developed iteratively, starting with research into common succession artifacts and business readiness criteria, followed by prototyping the workflow engine, building the first version of the AI assistant, and testing the scoring algorithm with early users.

To steer the AI and avoid vague suggestions, Huddly AI will use a combination of:

• Predefined business logic rules based on SME type and stage
• Tagging systems for uploaded documents to track completeness and categorize gaps
• A metadata model that informs the AI about user progress and context (e.g. business type, industry, missing artifacts)

This ensures the AI assistant gives context-relevant, high-impact prompts rather than generic advice.

3.2 Nieuwheid / Uniek Karakter

While several online platforms exist to facilitate business acquisitions—such as BizBuySell, BusinessesForSale.com, Empire Flippers, and Flippa—these focus almost exclusively on buyers, prioritizing deal listings and investor support. In contrast, Huddly AI centers the seller’s experience, addressing an underserved but critical pain point: the unpreparedness of SME owners to exit their business smoothly.

Our unique value proposition combines three integrated elements:

1. Succession Planning Support: A guided process to collect, improve, and structure essential documentation (financials, legal, operations, etc.) using AI-driven workflows.
2. Readiness & Handoff Tools: A proprietary readiness score and AI-assisted support for building Standard Operating Procedures (SOPs) and internal knowledge transfer assets to ensure business continuity.
3. Seller-First Approach: Unlike existing solutions, Huddly AI is built for business owners—not investors. It provides a safe, empathetic, and accessible environment to plan their exit and secure their legacy.

This integrated and seller-centric approach is not currently offered by any known competitor, either in the Dutch market or internationally.

3.3 Technische Knelpunten:

The key technical challenge for Huddly AI lies in translating the nuanced business logic of succession planning into a dynamic, adaptive digital workflow that can guide SME owners in a scalable yet personalized way. Because every business is different—varying in size, documentation quality, ownership structure, and readiness—there is no one-size-fits-all journey.

Specific technical bottlenecks include:

1. Context-Aware Workflow Orchestration:
   Designing a system that can dynamically tailor the workflow to each user’s context, determining which artifacts are needed and in what order—while adapting in real time as new information is added.
2. Readiness Score Development & Validation:
   Developing a scoring algorithm that evaluates completeness and quality across four key pillars (Finance, Operations, Continuity, Legal), while also motivating user progress and providing buyers with meaningful insight. Ensuring the score is both transparent and trusted by users and external stakeholders is a key technical and behavioral challenge.
3. Proactive AI Assistant Integration:
   Integrating LLM-driven agents that can interact conversationally (via text or voice), interpret context (e.g. files being viewed), and proactively recommend high-impact next steps—all while remaining user-friendly and intuitive.
4. Artifact Quality Assessment & Contradiction Handling:
   Automatically assessing uploaded documents and identifying gaps or inconsistencies (e.g. mismatched financial figures across PDFs or Excel files), while guiding users toward corrective action.
5. Scalability & Interoperability:
   Ensuring all components (LLMs, algorithmic scoring, UI workflows) communicate seamlessly as a unified system, and designing the platform architecture to scale across diverse business types and user profiles.

These interrelated hurdles justify a structured feasibility study focused on validating both the technical underpinnings and the user experience needed for successful real-world adoption.

4. ECONOMISCH PERSPECTIEF (Economic Potential)

4.1 Doelgroep en Probleem:

Huddly AI targets small business owners, particularly in the SME segment with 2–50 employees, who are nearing retirement or considering a sale. These owners typically have built their business from the ground up but lack the tools, knowledge, and support to exit successfully.

The core problem is not the lack of buyers—it’s the absence of a structured, seller-friendly succession process. Most owners:

• Have never sold a business before and may only go through this once in their lifetime.
• Lack clear guidance on what documents to prepare, what buyers expect, or how to create continuity after a sale.
• Fear deals falling through due to missing or poor-quality documentation, inconsistent operational practices, or unaddressed knowledge transfer.
• Lack external support to navigate the emotional and technical complexity of preparing their business for handoff.

As previous research shows, the majority of SME owners are not succession-ready—leading to failed handovers and lost opportunities. Huddly AI support owners with structure, clarity, and practical tools for exit readiness.

The team has conducted early-stage interviews with investors and M&A professionals. While direct validation with business owners is planned in this project, these experts confirmed the platform’s value and the lack of existing seller-side tools.

In addition to interviews and advisory input, we analyzed real-world discussions on forums like Reddit where small business buyers and sellers openly share their frustrations. Common themes include:

• Owner-dependence: Many businesses are essentially “one-person shows” and difficult to transfer.
• Poor documentation: Buyers are wary due to missing or messy financial records.
• No succession plan: Sellers often wait too long, leaving no time to prepare.
• Broker distrust: Sellers dislike high fees and lack of transparency.
• Fragmented platforms: There’s no “Zillow for businesses”—the process is manual and opaque.

These unfiltered user perspectives highlight the need for a platform like Huddly, which gives sellers structure, readiness tools, and independence in preparing for sale—without immediately involving brokers.

The feasibility study will involve deeper testing with SME owners to validate pricing, workflow, readiness scoring, and AI usability.

4.2 Marktpotentie

​Understanding the market potential for Huddly AI requires a thorough examination of small and medium-sized enterprises (SMEs) and the prevalence of business transitions in the Netherlands, Europe, and globally.​

Netherlands:

• Total Businesses: As of 2022, the Netherlands had approximately 2 million businesses. ​Centraal Bureau voor de Statistiek
• Family-Owned Businesses: Approximately 61% of companies with >1 employee qualify as family businesses, with nearly 300,000 employing multiple people. ​Centraal Bureau voor de Statistiek
• In Zuid-Nederland, the urgency is even greater: over 65% of SMEs in Limburg and Zeeland are family-owned, with many led by aging entrepreneurs nearing retirement.
• Succession Planning Challenges: A significant number of these family businesses lack formal succession plans, posing risks to business continuity and employment.​

Europe:

• SME Prevalence: SMEs constitute 99% of European businesses, providing employment to more than 85 million citizens. ​single-market-economy.ec.europa.eu
• Business Transfers: Each year, approximately 450,000 firms with 2 million employees are transferred in Europe. However, around 150,000 businesses risk unsuccessful transfers annually, potentially endangering about 600,000 jobs. ​
• Family Business Transitions: Within the next decade, nearly 40% of European family-owned businesses anticipate a transition in leadership or ownership by 2035, yet only 30% have established formal succession plans. ​

International:

• In the U.S., over 90% of small businesses are family-owned or could become family-owned.
• Global Succession Crisis: By 2030, it is projected there will be a global shortfall of over 50 million successors for SMEs, due to demographic changes and a declining interest in business ownership among younger generations. ​

Market Opportunity: The data underscores a substantial market opportunity for Huddly AI, particularly in the Netherlands and broader Europe, where a significant number of SMEs are approaching transition phases without adequate succession plans. By providing a structured, AI-driven platform to facilitate these transitions, Huddly AI can address a critical need, ensuring business continuity and preserving employment.​

Next Steps: To further refine our market analysis, we need to continue validating our customer base through the following activities:

• Targeted Research: Conducting surveys or interviews with SME owners to gain insights into their succession planning needs and challenges.​
• Competitive Analysis: Identifying existing solutions in the market and evaluating how Huddly AI can differentiate itself.​
• Regulatory Considerations: Understanding legal and financial regulations related to business succession in target markets to ensure compliance and relevance.​

By delving deeper into these areas, we can better position Huddly AI to effectively serve SMEs in navigating their succession planning processes.

4.3 Kansen en Bedreigingen

This section outlines the competitive landscape, key market opportunities, and external threats that could influence Huddly AI’s development and adoption trajectory.

Competitor Table:

Opportunities:

• Rising urgency in Zuid-Nederland: Demographics and local pilots show massive need for structured succession tools
• Underserved seller market: Most platforms focus on buyers or advisors—not the SME owner as primary user
• SME willingness to pay: Owners currently spend thousands on advisory, templates, or marketplaces—Huddly meets them in the middle
• Ecosystem integration potential: Huddly could partner with chambers, accountants, legal techs, and M&A brokers to expand reach

Threats:

• Partial substitutes exist: DIY apps and advisors already provide support—differentiation via workflow orchestration and AI is key
• Digital literacy gaps: Older SME owners may struggle to adopt digital tools without support
• AI trust challenges: Readiness scoring must be seen as credible, not arbitrary
• Market education required: Many owners delay succession until it’s too late—Huddly must spark early action

4.4 Verdienmodel en Terugverdientijd

Huddly AI will generate revenue through a hybrid model

1. Freemium Onboarding:
   New users can complete basic onboarding and receive a preliminary readiness score for free, lowering friction. Research shows that comparable Dutch platforms (e.g. OvernameAdvies.nl) also use freemium + success-fee models, validating this approach.
2. Subscription Tier (MVP Test Phase):
   During the feasibility phase, we plan to test monetization with three user segments:
   • 25 early adopters paying €20/month
   • 10 pilot partners at €50/month
   • 5 premium testers at €100/month
     Over 3 months, this results in a projected total revenue of €4,500, offsetting part of the feasibility study costs.
3. Success-Based Fee (Post-MVP):
   After platform validation, a transaction-based success fee will be charged upon successful handover or sale. This aligns incentives with platform performance and offers long-term revenue potential.

Payback Period & Financial Estimates:

• Estimated MVP Development Cost: €74,700
• Scalable Revenue Potential: Early projections suggest acquisition of 1,000 users within the first 6–12 months, significantly improving ROI and enabling reinvestment into platform enhancements, partnerships, and expansion.
• Conservative User Forecast: 100 users × €100/month × 8 months = €80,000 revenue
• Expected Time to Recoup Investment: 8 months (conservatively)

This cost-revenue alignment indicates that Huddly AI could recoup its investment through early-stage monetization within 6 to 12 months, especially if the pilot confirms user willingness to pay and adoption levels. Following feasibility validation, we will pursue additional funding (venture or public) to scale the platform, build new features, and expand into adjacent EU markets.

One of the core feasibility questions to be tested during the project is whether this pricing model aligns with user willingness to pay—especially among sellers who may be cost-sensitive or skeptical of digital platforms.

Follow-up investment:
Post-feasibility, the team will seek additional funding (venture or public) to scale across Europe, expand AI capabilities, and deepen partner integrations.

4.5 Financiële Knelpunten

As a bootstrapped startup, Moving Data Insights must spend conservatively. Without support:

• User testing would be minimal, increasing the chance of misaligned development
• The team would need to build a simpler MVP that doesn’t validate the core innovation (e.g. scoring, AI-guided workflows)
• Risk of building the wrong thing—and burning limited time and resources—would be high

This would jeopardize the opportunity to validate critical assumptions around user behavior, AI integration, and readiness scoring. A public subsidy allows the team to take a research-driven, user-centric approach, increasing the chances of developing a successful and scalable innovation.

Without public support, the innovation risks never reaching market fit—not because the need isn’t real, but because the tools to test and validate it would remain out of reach. Co-funding ensures this opportunity to strengthen SME resilience isn’t lost.

5. HAALBAARHEIDSVRAGEN (Feasibility Questions)

This section outlines the key assumptions and corresponding feasibility questions that will guide the research activities. These questions are designed to validate technical, behavioral, and economic aspects of the platform before full-scale development.

5.1 Aannames en Hypotheses:

1. SME owners are willing to engage with an AI-supported platform to prepare their succession plan.
2. The target group has sufficient digital literacy to complete the onboarding and planning workflow.
3. Users have uneven access to the required documents, and this affects their ability to complete the workflow.
4. A hybrid pricing model (monthly subscription + success fee) is acceptable and financially sustainable.
5. Users will trust and be motivated by a readiness score generated by the system.
6. Personalized, AI-guided workflows are more effective and engaging than static templates or generic checklists.

5.2 Haalbaarheidsvragen:

1. What percentage (%) of SME users who begin onboarding complete the workflow without assistance?
2. What proportion of target users demonstrate sufficient digital literacy to navigate the platform independently?
3. Which types of documents are most often missing or incomplete, and how does this impact user progress through the workflow?
4. What percentage (%) of SME owners express willingness to pay for the platform, and how does this align with the proposed pricing model?
5. How do users and M&A advisors perceive the credibility, clarity, and motivational value of the readiness score?
6. To what extent do personalized, AI-guided workflows increase user task completion rates compared to static checklists or templates?

6. TECHNISCH EN FINANCIEEL RISICO (Risks)

6.1 Technical Risks

Huddly AI requires the development of several non-trivial technical components:

• A dynamic, personalized workflow engine that adapts to each user’s business context.
• A readiness scoring algorithm that interprets uploaded artifacts and reflects both completeness and quality across four key domains.
• An AI-based assistant that provides context-aware guidance through voice or chat.

These elements must work together seamlessly, and each presents technical uncertainty—particularly in ensuring trust, clarity, and usability for non-technical users. To our knowledge, there is currently no off-the-shelf solution in the Dutch or EU market that combines AI-guided workflows, dynamic readiness scoring, and seller-side support into an integrated succession planning tool. Existing tools tend to focus on document storage or buyer matchmaking, not structured seller enablement. Without validation, there is a high risk of investing in a platform architecture that fails to meet user expectations or is too complex to scale effectively.

6.2 Financial Risks

As a bootstrapped startup, early development funding must be spent carefully. Without validating user willingness to pay, digital readiness, and document access, any investment in full development could lead to sunk costs and product misalignment. Misjudging these factors could result in rework, lost time, or failure to reach market fit.

6.3 Public Co-Funding Justification

The technical and market risks are high enough that private investment alone is difficult to justify at this stage—yet the societal and economic benefits (e.g. enabling succession, preserving jobs, empowering SMEs) are significant. Public funding helps de-risk the innovation, enabling a structured feasibility study that determines whether a scalable, trusted platform is viable before larger investments are made. Without this support, the innovation may never be validated or built.

7. UITVOERBAARHEID (Feasibility)

7.1 Beschrijving van de Projectactiviteiten

The Huddly AI feasibility project will run for 6 months and consists of seven work packages:

• WP1: Technical Architecture & Platform Setup: Define platform architecture, modules, and technology stack.
• WP2: Business Logic & Workflow Mapping: Co-design document collection workflows and decision logic for AI.
• WP3: Software with AI Chatbot & Scoring Logic Development: Build software platform with readiness scoring framework and conversational AI prototype.
• WP4: User Interviews & Field Research: Conduct qualitative testing with SME owners on usability, trust, pricing.
• WP5: Early MVP Launch: Deliver testable MVP, track onboarding, AI engagement, and feedback.
• WP6: Funding & Go-to-Market Strategy: Design financial model, co-funding opportunities, and outreach plan.
• WP7: Readiness Audit & Final Validation: Evaluate MVP success based on user progress and scoring outcomes.

7.2 Projectplanning

Type key: HLB = Feasibility Study (Haalbaarheidsstudie) Research to assess technical or economic viability of an innovation project.
Includes user research, market validation, pricing studies, go-to-market planning. IO = Industrial Research (Industrieel Onderzoek) Systematic research to gain new knowledge aimed at developing or improving products, processes, or services. EO = Experimental Development (Experimentele Ontwikkeling) Use of existing knowledge to build or test prototypes, MVPs, or pilots — includes user testing and iterative improvement.

7.3 In te huren expertise

The core project team brings a strong mix of technical, business, and market development skills:

• Adam Broniewski Brings deep expertise in lean startup development, technical architecture, and AI-driven product design. He has previously led feasibility projects, built scalable data platforms, and specializes in turning business logic into functional digital workflows.
• Brett Nakonechny Brings a strong network of venture capital investors, and experience in M&A. He supports market validation, pricing strategy, and business model design, with a background in managing founder-investor platforms.
• Fatima Nakonechny Has professional experience in lead generation, marketing, and user engagement testing. She will support the design and execution of the feasibility interviews and usability testing with SME owners.

In addition, the team is actively supported by mentors from The Gate (TU/e’s startup hub) and IE Venture Lab (IE Business School), providing strategic guidance in product-market fit, fundraising strategy, and international growth planning.

Despite this strong foundation, the following expertise needs to be contracted externally due to their technical depth, legal complexity, or time constraints:

• Legal & Tax Advisors
  To ensure the platform’s document workflows and scoring logic comply with Dutch and cross-border legal norms for SME transfers, we will engage a legal firm experienced in M&A and family business law. This expertise is not present in-house, and legal accuracy is critical for user trust and adoption.
• Data Protection & GDPR Consultants
  We will contract a boutique GDPR consultancy or freelance expert to validate our data handling and onboarding flows. Although familiar with GDPR, we require third-party validation to mitigate compliance risks and strengthen user confidence.
• Software Security Experts
  To test MVP vulnerabilities—particularly around document uploads and user data—we will hire a freelance cybersecurity auditor or ethical hacker. This is essential due to the sensitive nature of succession data and our limited in-house security expertise.
• Freelance Developers (TU/e-affiliated)
  We will hire TU/e-affiliated developers to support modular MVP development, focusing on AI integration and dashboard components. This offers cost-effective access to high-quality local talent and complements our core technical team.
• UX/UI Designers
  To design an accessible onboarding flow and dashboard experience for non-technical SME users, we will engage freelancers or agencies with experience in Dutch B2B and GovTech design. Our in-house team lacks dedicated UI/UX capacity for this audience.

This combination of in-house leadership and targeted external support ensures that the project can move forward efficiently, while meeting all legal, security, and usability standards required for a successful and trusted digital succession platform.

7.4 Vervolgproces na het Project

• Further Product Development:
  Learnings from MVP testing will inform full product development in months 7–12. This includes deeper AI feature refinement, dashboard improvements, and expansion of document workflows.
• Hard Launch (Month 12):
  A fully validated platform will be launched to a broader audience with a structured go-to-market strategy.
• Buyer-Side Expansion:
  Focus will shift to onboarding investors and institutional buyers and integrating their needs into the platform.
• Ongoing Partnership Building:
  Outreach to marketplaces, legal/accounting firms, and SME networks to embed Huddly AI into the broader succession ecosystem.
• Funding:
  The team will pursue additional funding (private or public) to scale development, grow the team, and expand geographically.

7.5 Risicoanalyse Uitvoering

8. PASSENDHEID BIJ DOELSTELLING (Alignment with Grant Objectives)

8.1 Locatie & Regionale Impact

All activities will be carried out in Eindhoven, within the Zuid-Nederland region. This location was chosen strategically due to:

• Proximity to Eindhoven University of Technology (TU/e), providing technical talent for AI, software engineering, and prototype development.
• Access to the startup support ecosystem via The Gate, including mentorship, coaching, and regional business networks.
• A dense population of family-owned SMEs across Limburg, Noord-Brabant, and Zeeland, enabling practical user testing with succession-vulnerable businesses.

The project directly contributes to Zuid-Nederland by:

• Strengthening economic resilience through higher succession success rates among SMEs.
• Supporting regional employment continuity by helping prevent unnecessary business closures.
• Boosting the innovation ecosystem by linking academic talent, AI technology, and practical regional challenges.

The feasibility study ensures that knowledge and value creation remain anchored in Zuid-Nederland, with tangible benefits for regional businesses, workers, and startup infrastructure.

8.2 Bijdrage aan KIA & Missies

This project aligns with the following Kennis- en Innovatieagenda’s (KIA’s):

KIA 8 – Maatschappelijk Verdienvermogen

The core purpose of Huddly AI is to support inclusive economic transitions by helping small business owners—particularly aging founders of family-run SMEs—prepare for succession. The platform reduces value loss and increases economic resilience by enabling:

• Continuity of employment and productivity
• Preservation of business legacies
• Smooth integration of next-generation ownership

Strategic alignment and intended outcomes:

• Regional resilience: By increasing the rate of successful business handovers, Huddly supports job retention and economic continuity in Zuid-Nederland—especially in areas with high SME concentration.
• Societal value creation: Huddly helps preserve soft assets like customer relationships, craftsmanship, and local economic heritage—key elements in sustainable regional ecosystems.
• Reducing systemic risk: With succession planning failures already causing ~2% job loss annually, Huddly mitigates the risk of widespread business closure and intergenerational economic disruption.

Relevant mission themes within KIA 8:

• Aging in place / Future-proof working: Huddly enables older entrepreneurs to exit on their own terms, reducing mental and physical stress while transferring knowledge and responsibility to the next generation.
• Sustainable economic growth: By strengthening the transferability of SME value, the project contributes to preserving GDP, employment, and entrepreneurial capacity in the Dutch economy.

KIA 7 – Digitalisering

Huddly AI applies cutting-edge AI and data-driven workflows to a highly under-digitalized challenge: SME succession planning. Most small business owners still rely on informal records, verbal knowledge, and outdated processes. Huddly brings modern digital infrastructure to this context.

Strategic alignment and intended outcomes:

• Accelerating digitalisation in traditional sectors: The platform makes digital tools—especially AI—accessible to non-technical users through a conversational assistant and structured guidance.
• Strengthening digital autonomy: By capturing business-critical knowledge in structured workflows, Huddly empowers SME owners to take control of succession without external dependency.
• Enabling digital inclusion: The design prioritizes usability for older, less tech-savvy users, promoting digital confidence and trust.

Relevant programming lines from KIA 7:

• AI for socially relevant use cases: Huddly applies AI to a tangible societal issue—business continuity and employment preservation—rather than speculative or experimental use.
• Human-centered ICT: The platform is designed for real-world usability, with AI recommendations grounded in the user’s context, business type, and document readiness.
• Data & semantic modeling: The platform converts unstructured SME knowledge into structured, machine-readable workflows and metadata models to improve decision support.

Use of Key Enabling Technologies (Sleuteltechnologieën):

• Artificial Intelligence (AI)
• Data analytics and semantic modeling
• Human-centered ICT

These technologies are applied not as abstract R&D, but in service of a concrete, socially urgent challenge—fully in line with the ambitions of both KIA 7 and KIA 8.

8.3 Geen Reguliere Bedrijfsvoering

This project is not part of the regular business operations of Moving Data Insights. The company primarily delivers contract-based data analytics solutions to external clients, often focused on short-term insight delivery and dashboarding. While there has been exploration of different innovation avenues over the past two years—including work on MobilityDB and other technical prototypes—these efforts were experimental in nature and did not involve full product development.

Huddly AI represents a clear pivot: the creation of a standalone software platform designed for broad user adoption, combining AI, workflow orchestration, and strategic business consulting into a unified product. It moves beyond analytics services into full-stack product development and user-focused platform design, which is a significant departure from the company’s normal consultancy-style operations.

Without this grant, the company would lack the capacity to rigorously test, validate, and build such an ambitious tool, making public co-funding essential to pursue this innovation path.

9. BEGROTING EN FINANCIERING (Budget & Financing)

This section provides a breakdown of the expected costs, revenue offsets, and financing structure for the feasibility project. It includes internal and external costs, detailed justifications, anticipated revenue during testing, and a financing overview aligned with MIT Zuid requirements.

9.1 Begroting per Kostensoort

The following table provides a breakdown of the total project costs, categorized by personnel expenses, external advisor costs, and projected revenue offsets. It distinguishes between eligible and non-eligible costs in accordance with the subsidy scheme for Zuid-Nederland.

### **9.2 Toelichting per Kostensoort**

This table details the underlying calculations for each activity in the project, showing the estimated number of hours, hourly rates, and resulting internal and external costs. It also clarifies how different expert roles contribute to the feasibility study and why their involvement is necessary to achieve the project goals.

The following table outlines the projected revenue generated during the feasibility project through paid user testing. It segments user types by pricing tiers and participation length, providing a realistic estimate of short-term income from early adopters and pilot users.

This table details the non-eligible project expenses, such as third-party software tools, cloud services, advertising, and compliance support. These are necessary for development, testing, and market validation, but fall outside the subsidy’s reimbursable cost categories.

9.3 Financieringsinzicht (Per Financier)

The following table outlines how the total eligible costs will be financed. It shows the applicant’s own contribution and the requested MIT Zuid subsidy. There are no other co-financing sources applicable.