Project Title: Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office

Paier

Details
Project Title Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Project Topics Artificial Intelligence & Machine Learning Budgeting, Forecasting, and Cost Optimization Data Management Digital Marketing Entrepreneurship Growth Strategy Innovation Marketing Operations PR & Communications Product Design & Development Reporting, Financial Planning & Analysis Research & Development Research, Analysis, Evaluation Sales & Business Development Software Design & Development Strategic Planning
Skills & Expertise AI-Assisted Prospecting Campaign Design Competitive Research CRM Analysis Customer Acquisition Customer Discovery Executive Communication and Presentation Design Experimentation and Hypothesis Testing Generative AI and AI Agents Go-to-Market Strategy Interview Design KPI Development Market Research Persona Development Positioning Product Strategy Prompt Engineering Roadmapping Sales Strategy Segmentation Spreadsheet Analysis Value Proposition Design
Project Synopsis: Challenge/Opportunity
Paier is an early-stage, AI-native financial technology company building a new way for businesses and financial professionals to run the financial back office. At the center of the platform is Bob from Accounting, an AI agent that helps capture financial activity, organize work, prepare transactions and reporting, support the month-end close, forecast cash, and answer questions about the business.

Paier combines core accounting infrastructure with forward-looking financial planning and operational workflows. Its operating principle is simple:

Bob drafts. A person approves.

Paier is now at an especially important stage of growth. The company has begun onboarding early customers and is seeing meaningful interest from financial professionals such as fractional CFOs, controllers, bookkeepers, accountants, and firms that manage financial operations for multiple businesses.

That creates an intriguing go-to-market opportunity. Instead of acquiring every small business individually, Paier may be able to reach businesses through professionals and firms that already manage portfolios of clients and influence the technology those clients use.

At the same time, this is still a hypothesis. Other segments, customer problems, positioning strategies, channels, and partnership models may prove equally or more attractive.

That is what makes this a valuable live case.

Paier does not need another theoretical marketing plan. It needs evidence about:
  • Which customers or channels have the strongest need for Paier
  • Which problems create the greatest urgency
  • Which value propositions and messages resonate
  • Which acquisition and partnership strategies are practical for an early-stage startup
  • Which objections or adoption barriers matter most
  • Which market signals should influence Paier's product, integrations, onboarding, pricing, and roadmap
  • How Paier can turn early traction into a repeatable growth engine
Teams will act as market researchers, growth strategists, product thinkers, and startup experimenters. They will investigate Paier's potential markets, develop and compare strategic hypotheses, identify a recommended beachhead, design go-to-market experiments, and use evidence to improve their recommendations.

Teams are strongly encouraged to go beyond desk research where practical. This may include customer interviews, expert conversations, messaging tests, market-facing experiments, and responsible outreach to qualified prospects. Direct outbound outreach is encouraged but is not required to participate in or remain eligible for the competition.

The goal is not to turn students into a sales force. The goal is to learn what happens when strategic assumptions encounter real market evidence.

The central challenge:

How can Paier identify, validate, and scale the right go-to-market strategy for its AI-native financial platform while using real market feedback to strengthen its positioning, product roadmap, customer acquisition model, and long-term growth?

Where Paier Is Today

The Platform

Paier's capabilities include:
  • Double-entry accounting infrastructure, including trial balance, P&L, balance sheet, bank reconciliation, and month-end close
  • Accounts payable workflows from invoice capture through coding, approval, and payment
  • Cash-flow forecasting and close-management workflows
  • Firm-level functionality that allows finance professionals to work across multiple client businesses
  • Shared documents, information, and communication between firms and clients
  • Web and mobile experiences
  • AI-assisted financial workflows through Bob
Integrations

Paier's integration landscape is evolving quickly.

A separate Paier Integration Roadmap in the competition Resource Library should be treated as the source of truth for what is currently live, rolling out, under development, or being explored.

Teams should not represent an integration, feature, pricing commitment, or roadmap item as available unless it appears in Paier's current competition materials.

Coming soon, so please do not pitch these capabilities: Daily Pay and Tap to Pay.
Project Synopsis: Activities/Actions Required
  1. Find the Beachhead

    Analyze Paier's market and identify the customer or channel segments with the greatest potential.

    Compare segments such as fractional finance firms, bookkeeping and accounting firms, small and midsize businesses, larger organizations with fragmented finance systems, AI-forward finance firms, and firms adopting AI-native financial infrastructure.

    Evaluate segments based on factors such as:
    • Customer pain
    • Market size
    • Reachability
    • Adoption readiness
    • Revenue potential
    • Buying behavior
    • Competitive intensity
    • Distribution leverage

      Strategic fit with Paier: Do not assume that Paier's current hypotheses are correct. Use evidence to determine where Paier can win first.

  2. Build the Wedge

    Develop a sharp positioning and value proposition for the highest-potential audiences.

    Determine:
    1. What problem Paier should lead with
    2. Which benefits and outcomes matter most
    3. Who the economic buyer and primary user are
    4. Which proof points create trust
    5. Which objections are likely to arise
    6. How Paier should differentiate from accounting software, fintech platforms, AI tools, and existing workflows
    7. Which messages and offers are most likely to create interest and action

  3. Build the Growth Machine

    Translate the strategy into a focused customer-acquisition and partnership model.

    Identify the channels, sales motions, partnerships, AI-assisted workflows, and experiments Paier should prioritize.

    Teams should define the assumptions their strategy depends on and design fast, practical ways to test them.

    Possible methods include:
    • Customer discovery interviews
    • Messaging tests
    • Prospect research
    • AI-assisted segmentation and personalization
    • Limited outbound campaigns
    • Partnership conversations
    • Landing-page or campaign concepts
    • Pricing and packaging conversations
    • Surveys
    • Expert interviews
    • Other appropriate market experiments

  4. Enter the Market

    Test important assumptions using the strongest evidence available. Teams are strongly encouraged, but not required, to conduct direct market-facing validation.

    Teams choosing to conduct outreach should have a clear ICP, hypothesis, and message before contacting prospects. Teams are encouraged to use Paier office hours to pressure-test their approach before beginning.

    Within the competition's stated guardrails, teams do not need individual approval for every prospect or every message.

    The objective is to learn, not to generate sales. Document:
    • What you tested
    • Why you tested it
    • Who or what you tested it with
    • What happened
    • What surprised you
    • Which assumptions were supported
    • Which assumptions were challenged
    • What your team changed because of the evidence

      Teams that do not conduct outbound outreach should still seek credible evidence through customer discovery, expert conversations, research, message testing, surveys, or other appropriate validation methods.

  5. Convert Signal Into Scale

    Turn the accumulated evidence into an actionable 30 / 90 / 180-day growth roadmap for Paier.

    Connect your recommendations to:
    1. Customer acquisition
    2. Positioning and messaging
    3. Partnerships
    4. Product priorities
    5. Integrations
    6. Onboarding
    7. Pricing and packaging
    8. Customer experience
    9. Operational priorities
    10. KPIs and expected impact
Project Synopsis: Expected Results
Success means moving from assumptions to evidence and producing recommendations Paier can actually use.

By the end of the competition, strong teams will:
  • Identify and rank 2 to 3 high-potential customer or channel segments using a clear evaluation framework
  • Develop at least two meaningful market hypotheses and rigorously test at least one
  • Gather credible outside evidence through methods such as interviews, market conversations, expert input, messaging tests, surveys, outreach, or other experiments
  • Record negative signals and invalidated assumptions as carefully as positive ones
  • Surface at least three actionable insights Paier can use to improve its positioning, customer experience, product roadmap, integrations, or acquisition strategy
  • Recommend a prioritized 30 / 90 / 180-day roadmap with initiatives, sequencing, KPIs, dependencies, and expected impact
  • Submit a concise, evidence-backed Executive Pre-Read
  • If selected as a finalist, deliver a 10-minute executive presentation to Paier leadership and judges

Useful metrics may include, where relevant:
  • Response rate
  • Qualified conversation rate
  • Demo or follow-up interest
  • Channel-partner interest
  • Pain intensity
  • Message resonance
  • Acquisition efficiency
  • Time to value
  • Conversion intent
  • Experiment cost
  • Objection frequency
Judges should evaluate the quality of evidence, reasoning, and learning, not simply the volume of outreach performed.

Working With Paier's Market
Students participating in this competition are researchers and strategists, not Paier employees or commissioned sales representatives.

Teams May
  • Conduct customer and market research
  • Interview qualified prospects
  • Contact appropriate prospects by email or LinkedIn
  • Test positioning, messaging, and calls to action
  • Use AI to support research, segmentation, personalization, and analysis
  • Introduce an interested prospect back to Paier
  • Discuss the Paier concept using facts and materials provided in the competition
Teams Must
  • Clearly identify themselves as students participating in a Paier and CapSource live case competition
  • Stay within the factual claims provided by Paier
  • Respect professional communication norms
  • Ask permission before recording a conversation
  • Protect confidential or personally identifiable information
  • Keep prospect information and research within the team and competition environment
  • Refer genuine commercial interest back to Paier
Teams Must Not
  • Present themselves as Paier employees
  • Invent product capabilities, integrations, pricing, customer claims, or roadmap commitments
  • Negotiate contracts or commercial terms on Paier's behalf
  • Collect payment
  • Request confidential financial information from prospects
  • Use real Paier customer financial data
  • Text prospects
  • Pitch Daily Pay or Tap to Pay
  • Contact prospects known to already be in active discussions with Paier

What Counts as Qualified Market Validation
These definitions apply to teams conducting direct customer discovery or outreach.

Qualified Prospect

A qualified prospect is a U.S.-based decision-maker or meaningful software influencer who:
  • Fits the team's clearly defined target customer or channel segment
  • Experiences, manages, or advises on recurring financial operations relevant to Paier
  • Makes or meaningfully influences financial software or workflow decisions
  • Is not already in an active Paier sales or partnership conversation
For teams targeting fractional finance, bookkeeping, CPA, or accounting firms, a strong qualified prospect will generally serve at least 10 small or midsize business clients on an ongoing basis.

Tax-preparation-only practices do not qualify unless they also provide recurring bookkeeping, close, payables, controller, CFO, or related financial-management services.

Qualified Conversation

A qualified conversation is a substantive live conversation of approximately 15 minutes or more in which the participant discusses:
  • How their financial workflows operate today
  • Current tools and alternatives
  • Pain points and unmet needs
  • Buying or adoption considerations
  • Reactions to relevant parts of Paier's value proposition or proposed approach
A "no," objection, or negative reaction can be just as valuable as a positive response when it produces useful evidence.

Project Timeline

Paier - Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Due Date
Activities
Deliverables
Status
Action
Mon, 10/12/26
STUDENT ON-BOARDING BEGINS (CASE DETAILS RELEASED)
No Deliverables
No deliverables are required for this action item.
Instructions:
Get an early look at the Fall 2026 Live Case Competition and the company challenge you will be solving.

Use this preview period to:

  • Familiarize yourself with Paier and the competition

  • Review the high-level business challenge

  • Begin learning about the financial technology and accounting landscape

  • Organize your team and prepare for the full case launch
Please note that it will take us some time to organize you into your team. You will not be able to see full details until you are officially organized onto your team within the platform. If you've been registered for more than 48 hours without being assigned to a team, please contact jordan@capsource.io

Teams

Team Name  Project Name  Team Members 
Misericordia’s Team Keystone Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
LWU Group 7 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lindsey Wilson University - Group 21 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Florida Tech Team # 1 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Florida Tech Team # 4 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Misericordia’s Business in the Front Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
The Cougar Collective Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Holy Angel University - Group 4 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lee Brand Builders Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Tour de Force Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lindsey Wilson University - Group 15 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Holy Angel University - Group 5 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Holy Angel University - Group 11 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
The Fellas' Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Florida Tech Team # 2 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Misericordia’s Strategists Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Draper 4D Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Misericordia’s Mercy Mindset Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Florida Tech Team # 3 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Triple Threat Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Misericordia’s Case Closed Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lindsey Wilson University - Group 10 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Catalyst Consulting Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Holy Angel University - Group 6 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lindsey Wilson University - Group 9 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Holy Angel University - Group 7 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Core 4 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Holy Angel University - Group 8 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lee Insight Innovators Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lee Customer Catalysts Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
LWU Group 4 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lee Value Visionaries Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Holy Angel University - Group 1 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lee Market Mavericks Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lee Strategy Studio Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office
Lindsey Wilson University - Group 4 Scaling Paier: Building the Go-to-Market Engine for an AI-Native Financial Back Office