AI pitch deck guide

Benchmark performance on the specific task you solve, ideally vs. human or incumbent baselines.

Benchmark: Show head-to-head comparisons against best available alternatives.

Volume and uniqueness of proprietary training or fine-tuning data.

Benchmark: Explain why competitors cannot easily acquire equivalent data.

Cost to serve one query or prediction, and how it changes at scale.

Benchmark: Gross margins compress as compute costs rise; target 60%+ at scale.

Revenue retained and expanded from existing customers.

Benchmark: AI SaaS: 110%+ NRR signals sticky, expanding use cases.

How quickly customers achieve meaningful outcomes after onboarding.

Benchmark: Shorter time-to-value correlates strongly with retention.

• Show proprietary data sources competitors cannot replicate
• Describe workflow integrations that create switching costs
• Quantify the feedback loop that improves your model over time

• Show evaluation benchmarks on real customer tasks
• Explain fine-tuning or RAG strategy vs. off-the-shelf APIs
• Address latency, reliability, and cost at scale

• Tie pricing to customer value, not just seats or tokens
• Show gross margin after infrastructure costs
• Demonstrate expansion revenue as customers adopt more workflows