5 Million Dollar AI Products VCs Are Literally Asking You to Build (Right Now)

In partnership with

VCs just dropped their shopping list

You know those moments when investors say “We’re looking for the next big thing in AI” — and you pretend to nod knowingly?

We actually found what they mean.

Here’s what YC, a16z, and Sequoia are drooling over — and how you can build it before someone else does

Startups who switch to Intercom can save up to $12,000/year

Startups who read beehiiv can receive a 90% discount on Intercom's AI-first customer service platform, plus Fin—the #1 AI agent for customer service—free for a full year.

That's like having a full-time human support agent at no cost.

What’s included?

• 6 Advanced Seats

• Fin Copilot for free

• 300 Fin Resolutions per month

Who’s eligible?

Intercom’s program is for high-growth, high-potential companies that are:

• Up to series A (including A)

• Currently not an Intercom customer

• Up to 15 employees

Apply now

Premium | Advertise | Enterprise

#1 Multi-Agent Ops Copilot for SMBs

Why VCs care: YC’s latest Requests for Startups highlights infrastructure for multi-agent systems — agent workflows that coordinate complex, repeatable business tasks.

What to build: a back-office copilot that runs daily checklists — billing, collections, ticket triage, inventory reorders — by orchestrating sub-agents that talk to your existing systems.

MVP Path:

1. Define 3 recurring workflows (e.g., overdue invoices, “stuck” support tickets, low stock).

2. Use LangGraph (or Guardrails + Celery) to orchestrate sub-agents.

3. Connect data sources: Postgres/MySQL, Gmail/Outlook, Stripe, Freshdesk/Zendesk.

4. Add retrieval via pgvector/Pinecone for SOPs and policy docs.

5. Add human-in-the-loop approvals via Slack buttons or email.

6. Monitor activity via OpenTelemetry and a simple Grafana dashboard.

7. Ship a daily “Ops Brief” email summarizing key updates.

Stack: OpenAI/Anthropic, LangGraph, Postgres + pgvector, Pinecone, Slack API, Stripe, Freshdesk.

Launch & Pricing: $500–$1,500/month per SMB; 5–10 clients → $2.5K–$10K MRR.

Risk: flaky automations — mitigate with approvals and replay logs.

(Source: YC RFS 2025 – “Infrastructure for Multi-Agent Systems”)

Want to build your own AI business? Access all our premium guides with a free trial:
👉 Start Free Trial

#2 Vertical Voice Agent (Phone + Webchat)

Why VCs care: a16z’s recent thesis on voice AI calls voice the next interface shift — a “wedge” into real workflows where chat falls short.

What to build: an AI voice agent for one vertical — property management, dental clinics, logistics — that answers calls, qualifies leads, books appointments, and follows up.

MVP Path:

1. Pick one workflow (e.g., “book a property viewing”).

2. Use Twilio for telephony and embed a WebRTC widget on your site.

3. Run OpenAI Realtime API or a VAPI-style stack for live two-way audio.

4. Define 10 intents with slot-filling and calendar integration.

5. Add “I’ll text you” fallbacks via SMS API.

6. Test with a 100-scenario QA bank to reduce errors.

7. Build a dashboard for transcripts and outcomes.

Stack: OpenAI Realtime/Whisper, ElevenLabs, Twilio, Redis for state, Google/Outlook calendars.

Launch & Pricing: $399–$899/month/location; 8–12 clients → $3K–$10K MRR.

Risk: compliance and accent issues; mitigate with consent and local models.

(Source: a16z “Voice Agents and the Next AI Platform Shift” 2025)

#3 Agent QA & Testbed Platform

Why VCs care: enterprise buyers demand agent reliability before deployment. Startups like Checkmate and ProtoAgent (YC 2025) are raising capital for automated AI stress testing.

What to build: a sandbox that bombards agents with stress, toxicity, and policy-edge cases — generating regression reports after every model update.

MVP Path:

1. Create an “adversarial scenario generator” (toxic, off-topic, policy violations).

2. Plug agent endpoints using OpenAPI.

3. Add scorecards: task success, latency, refusals, PII safety.

4. Include a 200-test baseline suite per client.

5. CI hook: rerun tests on every model or prompt update.

6. Add “diff” reports between model versions.

7. Export PDFs and Slack alerts for QA teams.

Stack: Python + FastAPI, pytest-style runners, S3 for logs, React dashboard.

Launch & Pricing: $1K+/month per client; 5 clients → $5K MRR.

Risk: keeping up with new model updates; mitigate with version pinning + nightly tests.

(Source: YC-backed agent QA startups; Sequoia AI infrastructure report 2025)

#4 Video-as-a-Primitive Ads Generator

Why VCs care: YC’s “Video Generation as a Primitive” thesis argues video is becoming the new HTML — a default content type across marketing and commerce.

What to build: an AI tool that turns a product URL into 15-second ads: auto-generating scripts, visuals, captions, and variants for TikTok, Reels, and Shorts.

MVP Path:

1. Input: product URL + brand colors.

2. Generate scripts from reviews and pages using RAG.

3. Combine assets + motion via Runway/Pika/Kling APIs.

4. Add voiceover (ElevenLabs) + captions (ffmpeg).

5. Output multiple aspect ratios and languages.

6. Include analytics (CTR and engagement).

7. Store variants in a brand dashboard.

Stack: OpenAI for scripts, Runway/Pika for visuals, ElevenLabs, ffmpeg.

Launch & Pricing: $499/month for 8 full length videos; 10 clients → $5K MRR.

Risk: quality inconsistency — mitigate with review queue + templates.

(Source: YC RFS 2025 – “Video Generation as a Primitive”)

#5 Memory & Retrieval Layer for Teams

Why VCs care: As context and long-term memory become bottlenecks, VCs are funding tools that act as “knowledge time machines” across teams and chats.

What to build: a team memory engine that ingests Gmail, Slack, and Drive, then answers “What did we decide about X?” with linked citations.

MVP Path:

1. Build connectors for Gmail, Drive, and Slack.

2. Chunk + embed documents; store via pgvector/Pinecone.

3. Route queries with a “decision extraction” prompt.

4. Return results with inline citations (no hallucination).

5. Send weekly “Decision Digest” emails.

6. Offer admin dashboards for retention + privacy.

7. Add API endpoints to push memory into agents.

Stack: LlamaIndex/LangChain, Postgres + pgvector, Pinecone, OAuth.

Launch & Pricing: $6–$12/user/month (min $300/month); 20–30 users → $6K–$9K MRR.

Risk: access scope + privacy; solve with least-privilege OAuth and optional on-prem mode.

(Source: Bessemer State of AI Report 2025; YC/Sequoia AI Infra Notes)

Go-to-Market: Fast Path to $5K MRR

• DM first: agencies, clinics, SMBs, Shopify brands (buy automation fast).

• Sell one clear outcome: “Book more calls”, “Clear invoices faster”, “Never forget a decision.”

• Start with 30-day paid pilots tied to success metrics.

• Convert pilots → 6-month retainers and upsell templates or analytics packs.

Tooling Cheat Sheet

• Reasoning/Agents: OpenAI (o1, Realtime), Anthropic (Claude), LangGraph

• Speech: ElevenLabs / Deepgram / Whisper

• Vector & Memory: pgvector, Pinecone

• Pipelines: Zapier/Make, Airflow for nightly jobs

• Comms: Twilio (Voice/SMS), Slack/Email APIs

• Video: Runway, Pika, ffmpeg

• Monitoring: OpenTelemetry, Grafana

Every few years, a shift happens quietly — the tools for building new billion-dollar companies become open-sourced, API-ready, and waiting for someone to wire them together.

Right now, that shift is happening in AI.

Each of these five products already has market pull and investor interest, meaning you don’t need to invent demand, just ship faster and package smarter.

Whether you’re an indie builder or a small studio, a single functional demo in one of these verticals could be your first $5K month or your next fundable company.

We hope you enjoyed this Latestly AI edition.
📧 Got an AI tool for us to review or do you want to collaborate?
Send us a message and let us know!

Was this edition forwarded to you? Sign up here

Premium | Advertise | Enterprise