Once a company decides it wants an AI agent that actually knows its internal data — not just a general chatbot — it usually lands on one of two approaches: a no-code builder for governed, custom agent workflows, or a ready-made assistant that plugs straight into the SaaS tools it already uses. StackAI and Dust each represent one of those paths, and they explicitly list each other as alternatives — a genuine head-to-head, not a stretch comparison.
StackAI
StackAI is a no-code, drag-and-drop platform for building AI agents that enterprises in regulated industries — healthcare, finance, legal — can actually get approved for internal use. The pitch is governance first: native audit logs, human-in-the-loop validation steps built into workflows, and deployment options that go all the way to fully on-premise or VPC, which is rare in this segment. It's model-agnostic, so you're not locked into a single LLM vendor.
Price: Free tier (500 runs/month, 2 projects). Enterprise pricing is custom, with unlimited projects and dedicated VPC/on-premise infrastructure.
Strengths: deployment flexibility that competitors rarely offer, governance and audit trails as a first-class feature rather than bolted on, human approval steps built into the workflow itself.
Limits: the free tier's 500 runs/month is really a trial, not something you'd run real work on; enterprise pricing requires a sales call; and against pure automation tools like n8n or Make, it doesn't compete on price.
Dust
Dust takes the opposite starting point: instead of building custom agent workflows from scratch, it plugs a ready-made AI assistant into the SaaS tools a company already runs — Slack, Notion, Google Drive, GitHub — so employees can ask questions and get answers pulled from real internal documents. It's multi-model (OpenAI, Anthropic, Google, Mistral), SOC 2 compliant, and already at real scale: 300,000+ agents deployed across 3,000+ organizations, backed by Sequoia Capital and reportedly already profitable on ARR.
Price: Free tier available. Pro roughly $29-30/seat/month ($24 if billed annually). Business around $99/month. Enterprise on request.
Strengths: ready-made connectors mean no internal engineering project to get started, real production scale and funding behind it, no single-vendor LLM lock-in.
Limits: per-seat pricing climbs fast for larger teams, there's no native on-premise deployment — worth checking carefully if you're in a heavily regulated industry — and for solo or occasional use, a plain ChatGPT subscription is simpler and cheaper.
StackAI vs Dust at a glance
| StackAI | Dust | |
|---|---|---|
| Core strength | Governed, custom agent workflows | Ready-made connectors to existing SaaS tools |
| Starting price | Free (500 runs/mo) → custom | Free → ~$29-30/seat/mo → $99/mo |
| Deployment | Multi-tenant, VPC, or fully on-premise | Cloud only (no native on-prem) |
| Best fit | Regulated enterprises, IT-governed rollouts | Teams already living in Slack/Notion/Drive/GitHub |
| Setup effort | Higher — you design the agent workflow | Lower — connect existing tools and go |
Verdict
Pick StackAI if you're in a regulated industry that needs on-premise or VPC deployment, native audit logs, and human-approval steps baked into agent workflows — and your IT team can own a real evaluation process rather than a quick signup. Pick Dust if you want employees asking questions against your actual Slack, Notion, Drive and GitHub content within days, not months, and cloud-only deployment isn't a blocker. Dust's free tier and transparent per-seat pricing make it the lower-friction way to find out if company-wide AI search is actually useful for your team before StackAI's heavier, governance-first setup is worth the investment.