Voker

What do they actually do

Voker is a self-serve web console that lets non‑engineers (product managers, designers, support teams) build, test, and deploy discrete AI features—called Vokers—without writing backend AI infrastructure code. The company positions this as a no‑code AI builder so product teams can ship AI features quickly rather than running an engineering project or operating a model stack themselves (YC profile, pricing).

Today, the product includes a no‑code builder and prebuilt templates/applets you can try in the browser, a GUI to configure prompts and structured outputs/guardrails (with a Create Voker Flow/Copilot that drafts configs from natural language), options to attach business knowledge (RAG), upload PDFs/images, and enable internet search, function calling and integrations, an in‑console Test/Execute view with debugging traces, deployable endpoints and shareable previews, and monitoring/analytics. Usage is tracked via credit‑based billing bundled with seats and Voker counts on self‑serve plans (demo applets, docs/changelog, pricing).

Early users appear to be SMB product teams in verticals like e‑commerce and proptech; YC lists Lull.com and Dutch.com as customers, and the site showcases e‑commerce and proptech‑oriented demos (YC profile, demo pages).

Who are their target customer(s)

• Product managers at startups and SMBs: They own feature delivery but lack time and engineering bandwidth to stand up models and infra. They need to ship AI features quickly without managing an ML stack or long implementation cycles.
• Designers and UX owners: They must prototype and validate AI interactions fast. They want to try prompts, inputs, and structured outputs in minutes and see real test traces without waiting for engineering to wire up prototypes.
• Customer support and success teams (e‑commerce, proptech): They handle repetitive questions and routing. They need self-serve ways to answer FAQs from docs/KBs and route messages without custom engineering.
• Operations/workflow owners: They need automations that perform actions (e.g., update records, call REST APIs) but are blocked by engineering requirements to make these flows safe and integrated.
• Small product‑led companies without ML platform expertise: They need production‑ready AI features with deployable endpoints, monitoring, and debugging, without building their own observability and infra.

How would they acquire their first 10, 50, and 100 customers

• First 10: Use founder networks and YC introductions to run hands‑on pilots (FAQ readers, message routers), offering free/discounted credits and white‑glove onboarding to ship a measurable feature within days (YC profile, pricing).
• First 50: Lean on self‑serve templates and deployable previews in e‑commerce/proptech plus a trial that spotlights Create Voker Flow; combine with targeted outreach to PM/design communities, short how‑to webinars, and 1–2 paid pilot slots per week to convert users who need light handholding (demo applets, docs/changelog).
• First 100: Scale via out‑of‑the‑box connectors and an integrations editor for common stacks, and recruit implementation partners (design/UX shops, SaaS integrators) to resell templates and run installs; formalize SMB packages and an enterprise path with SLAs and longer retention to land larger buyers (docs/changelog, pricing).

What is the rough total addressable market

Top-down context:

Voker sits at the overlap of low‑code/no‑code platforms (~$24.8B in 2023), conversational AI (~$11.6B in 2024), and IDP/document AI (~$2.3B in 2024), implying an upper‑bound opportunity around ~$38–40B, with overlap and enterprise-heavy spend that Voker may not target initially (Low‑code, Conversational AI, IDP).

Bottom-up calculation:

Example: 50,000 SMB product teams globally paying an average of $299/month (aligned to Voker’s Business plan) would yield ~$179.4M ARR; this is an assumption-based illustration, not a forecast (Voker pricing).

Assumptions:

• Roughly 50,000 SMB product teams globally are in-market for embedded AI features
• Average paid plan around $299/month per team (Business plan proxy)
• Voker can reach these buyers via self‑serve and light‑touch sales across SMB/mid‑market segments

Who are some of their notable competitors

• Retool: Low‑code platform for building internal tools and workflows; offers AI features, appealing to teams that might otherwise wire up AI and data sources with engineering support.
• Voiceflow: No‑code conversational assistant builder used by product and CX teams to design, test, and deploy chat-style assistants with knowledge and integrations.
• Botpress: Conversational AI platform for building chatbots and agents with flows, knowledge bases, and channel integrations; often used by teams wanting more control over assistant behavior.
• Langflow: Open‑source visual builder for LLM applications (drag‑and‑drop nodes for prompts, tools, and RAG); attractive to teams comfortable hosting and customizing their stack.
• Zapier: No‑code automation platform with AI features (e.g., AI Actions, chatbots) that connects to thousands of apps; competes for lightweight, action‑oriented automations without engineering.