Data
Ready to connect with your peers in data? Grab your free ticket for Startup Boston Week 2025 on Sept 8th - 12th today!
More sessions are still being added to the SBW2025 agenda!
All sessions are available BOTH in-person at Suffolk University and virtually.
STANDING OUT IN THE AI CROWD: STRATEGIES FOR REAL PRODUCT DIFFERENTIATION
Perfect for: founders, technical and founding engineers, AI product managers, investors, and go-to-market leaders looking to sharpen their AI strategy
With AI products flooding the market, building something technically impressive isn’t enough - you need to stand out strategically.
This panel will explore how startups can develop AI products that succeed not just through technological innovation but through smart market positioning, user experience, and business value, including:
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What makes an AI product truly unique beyond model accuracy and performance.
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Creating a competitive moat - whether building core AI technology or AI-wrapper solutions.
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Common pitfalls in AI product positioning and how to avoid them.
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Effective pricing, monetization, and go-to-market strategies for AI startups.
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How investors evaluate AI-wrapper startups versus deep-tech AI companies.
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Key trends shaping the future of AI product differentiation.
You’ll walk away with a clearer understanding of how to build an AI product that delivers value, resonates with users, and stands out in a crowded market.
DATA GOLD RUSH: MASTERING ACQUISITION AND ANNOTATION FOR AI SUCCESS
Perfect for: founders, founding engineers, early data hires, and anyone involved in data acquisition, operations, or AI product development
High-quality data acquisition and annotation are the backbone of any successful data-driven product.
This session will explore strategies for collecting and annotating data efficiently and cost-effectively, even on a startup budget, including:
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Best practices for acquiring diverse, high-quality data for AI/ML models
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How to balance the cost of data acquisition with the quality and quantity needed
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Key considerations for annotating data, especially for complex AI tasks like vision and NLP
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How to scale data acquisition and annotation while maintaining data quality
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Tools and platforms for streamlining data annotation and improving accuracy
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Ensuring ethical data acquisition practices and avoiding bias in datasets
You’ll walk away with actionable insights on how to build a scalable and reliable data foundation for your product - without breaking the bank.
AI YOUR WAY TO THE TOP: SMART TOOLS TO LAUNCH, SCALE AND AUTOMATE
Perfect for: early-stage entrepreneurs, solo founders, startup operators, small business owners, and freelancers looking to level up with AI
AI is a game-changer for entrepreneurs, helping them automate, optimize, and scale their businesses efficiently. This hands-on workshop explores practical AI tools for naming, branding, content creation, productivity, and automation.
Attendees will get live demos and actionable insights on integrating AI into their workflow - without breaking the bank, including:
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Best free AI tools for launching and growing a business.
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How to generate business names, branding, and domain ideas with AI.
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AI-powered content creation and productivity tools to save hours per week.
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Automating customer outreach, social media, and marketing with AI.
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No-code AI tools to eliminate repetitive tasks and improve efficiency.
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Best practices for integrating AI tools into a startup’s workflow—even without technical expertise.
You’ll leave with a toolkit of AI resources and strategies to streamline your business and focus on growth.
DATA FORTIFIED: BUILDING ROCK-SOLID AI FOUNDATIONS
Perfect for: founders, founding engineers, MLOps professionals, AI researchers, and anyone interested in building with an AI-first approach
Reliable AI starts with a solid data foundation. Creating or collecting content for AI applications requires more than just data gathering - it demands an AI-first approach to ensure quality, security, and scalability.
This panel will explore how to manage content, ensure data integrity, and protect against breaches or misuse while optimizing for performance and ethical AI practices, including:
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Core data quality and management practices to improve AI model performance.
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Best practices for creating and collecting AI-ready content.
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Managing data security, compliance, and governance while scaling AI applications.
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How to balance innovation with responsible data use and protection.
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The role of content management systems and metadata frameworks in building scalable AI.
You'll gain actionable insights into building a data infrastructure that supports reliable, scalable, and secure AI products.
BEYOND WORDS: UNLOCKING THE POWER OF MULTIMODAL AI
Perfect for: founders, technical and founding engineers, data scientists, ML engineers, investors, and AI product strategists
The next frontier of AI goes beyond text - multimodal models and advanced reasoning are reshaping AI applications.
This panel will explore how startups can integrate cutting-edge capabilities like vision, speech, and reasoning into their products to drive differentiation and user value, including:
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When and how to integrate multimodal AI (text, vision, audio) and reasoning to enhance products.
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Key technical challenges and cost considerations for deploying multimodal AI at scale.
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Model selection: off-the-shelf vs. fine-tuning—how to make the right call.
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UX strategies for improving user interaction with multimodal AI.
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Common misconceptions and emerging trends in multimodal AI.
You'll walk away with a deeper understanding of how to harness multimodality and reasoning to create smarter, more responsive AI products that stand out in a competitive market.
LLMOPS ON A SHOESTRING: SMART SCALING WITH VENDORS, APIS AND MICROSERVICES
Perfect for: founders, technical and founding engineers, MLOps professionals, AI product managers, and finance leads looking to build scalable AI products on a budget
Building scalable LLM applications is complex - but doing it on a startup budget is even tougher. This panel will explore cost-effective strategies for deploying, monitoring, and optimizing LLM-based applications by strategically leveraging vendors, APIs, and architectural components like databases and agents, including:
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The most cost-effective strategies for deploying and scaling LLM-based applications.
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Mission-critical expenses in the early stages and how budgets should evolve as the company grows.
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Evaluating vendors for LLM APIs, databases, and agents while minimizing lock-in risks.
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Leveraging architectural components like RAG, agents, and vector databases to enhance performance.
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When to use third-party APIs versus building in-house LLM infrastructure.
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Best practices for monitoring, observability, and troubleshooting LLM performance in production.
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Optimizing inference costs while maintaining responsiveness and reliability.
You'll leave with actionable insights on how to build a high-performing AI infrastructure without overspending—making smart trade-offs between performance and cost.
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Meet Hareesh Karthik! Hareesh is our Data & AI Track Lead for Startup Boston Week 2025. This is his third year on the Startup Boston Organizing Team.
Some fun facts about him: the next place on his travel bucket list is London. Look them up and connect with them on LinkedIn.