Dust
Dust builds custom AI agents wired into your company's Slack, CRM and docs, with shared team workspaces.
Dust makes the most sense for teams that want agents wired into real company systems with permissions and audit logs from day one, not bolted on later. The credit model is the thing to scrutinize: 8,000 credits on a Pro seat sounds generous until a deep-research agent or a tool-heavy workflow burns through them, and credits don't roll over. Mix Free and Pro seats across a workspace rather than buying Pro for everyone, and watch the overage cap an admin sets. If you want a single personal chatbot with no configuration, or you need flat-rate predictable billing, look at a single-assistant product instead.
Verified 7d ago · liveness 74/100 · cite: rightaichoice.com/tools/dust
- Ops teams (support, sales, marketing, data) wiring agents into real company systems
- Companies needing per-team data segmentation, SSO, SCIM and audit logs before broad AI rollout
- Teams that want to pick a different model per agent rather than one model everywhere
- Engineering and IT teams building incident response, ticket triage or self-service analytics agents
- Individuals wanting a single personal chatbot with no setup — the agent list, skills and permissions need real
- Small non-technical teams with no ops owner to build and maintain agents
- Buyers who need flat-rate predictable billing — credits vary by model and tool use, and don't roll over
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Skip Dust if you want a single personal chatbot with no configuration, or if you need flat-rate billing — credit consumption varies by model and tool use and doesn't roll over.
Running out of a seat's monthly credits only continues if an admin has enabled workspace overage, and then only up to a capped amount — so a heavy workflow can simply stop.
Per seat per month, Dust sits between a single-assistant subscription and a custom-built agent stack. Free seats at 0€ with 500 lifetime credits make occasional users genuinely free, Pro at 24€/seat/mo yearly (30€ monthly) suits most team members, and Max at 120€/seat/mo yearly (150€ monthly) is priced for power users running automations and deep research regularly — comfortably above $20/mo generic assistants but below assembling and maintaining your own orchestration layer. Enterprise is
In short
Dust — Dust builds custom AI agents wired into your company's Slack, CRM and docs, with shared team workspaces. Best for Ops teams (support, sales, marketing, data) wiring agents into real company systems, Companies needing per-team data segmentation, SSO, SCIM and audit logs before broad AI rollout, Teams that want to pick a different model per agent rather than one model everywhere. Free to start; paid plans from €24/user/mo.
What's new in Dust
Checked 7 days agoAcross the latest 5 updates: 2 feature updates and 3 news mentions.
Dust on measuring AI deployment ROI
Dust argues most companies measure AI deployment ROI wrong by counting saved hours against hourly cost, and proposes an alternative framing for evaluating agent deployments.
How to AI-pill an AI company
Dust published an AI-adoption playbook developed with Daniel Liem, based on the "AI Pilled" approach he built at Decagon.
Introducing self-improving skills: reusable AI capabilities that learn from usage
Dust shipped self-improving skills — reusable instruction sets that encode team expertise and adapt from usage rather than being rewritten by hand.
Dust welcomes Niji as an official partner
Niji, a European digital consultancy, became an official Dust partner, adding implementation expertise to Dust's partner network.
AI x Email: your agent lives in your inbox
Dust shipped a feature letting users loop any Dust agent into an email thread by forwarding messages to it like a colleague.
What people actually say about Dust — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
22 mentions across 6 sources (Hacker News, YouTube, Product Hunt, App Store, Stack Overflow, Lemmy), 64 more we could not attribute · researched Sep 29, 2026.
Weighted by the 86 posts each of 6 sources contributed.
- +70+ native connectors (Slack, Notion, Salesforce, Zendesk, GitHub) let agents act on real company systems
- +Per-agent model choice across 20+ frontier and open-source models enables cost/quality tuning
- +Dual-layer permission model separates what agents access from who can use them
- +US or EU data residency plus SSO, SCIM and audit logs address enterprise governance needs
- +Multi-agent orchestration with scheduled and event-driven triggers supports real operational workflows
- −No authentic community feedback exists in the scraped data to validate the tool's real-world reliability
- −Credits reset each period with no rollover, risking mid-month exhaustion for busy teams
- −Enterprise-only features (unlimited connectors, pooled credits, single-tenant) leave smaller tiers constrained
- −Name collision with games, novels and a messaging app makes independent research genuinely hard
- −Credit-based pricing is opaque: translating 8,000 credits into real agent runs is non-obvious
- • No credit rollover — unused credits vanish each billing period
- • Credit consumption per agent run is not transparently documented
- • Pooled and unlimited connectors require Enterprise, forcing mid-market upgrades
Viability Score
How well maintained and how widely used is Dust? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Custom agents with your own instructions, skills, knowledge and connected tools
- Choose a model per agent from 20+ frontier and open-source models (OpenAI, Anthropic, Google, Mistral, DeepSeek)
- Multi-agent orchestration with scheduled and event-driven triggers
- Self-improving skills that encode team expertise and adapt from usage
- Connect any agent to an email thread by forwarding messages to it
- 70+ connectors including Slack, Notion, Google Drive, GitHub, Salesforce and Zendesk
- Call external tools via native and remote MCP servers
- Frames: interactive dashboards and apps, white-labellable on Enterprise
- Pods: collaborative workspaces with shared context for people and agents
- Spaces for segmenting company data and permissions by team
- Dual-layer permission model separating agent data access from user access
- SSO via Okta, Entra ID and Jumpcloud, plus SCIM provisioning
- Audit logs, usage analytics and adoption reporting
- US or EU data residency; single-tenant deployment on Enterprise
- Developer API, Conversation API and Data Source API
About Dust
Dust is a platform for building custom AI agents that reach into your company's actual systems — Slack, Notion, Google Drive, GitHub, Salesforce, Zendesk and 70+ other connectors — rather than answering from a generic model. It calls its approach "multiplayer AI": people and agents working in the same workflow, with shared conversations, reusable skills and human review built in. The target buyer is the ops-minded builder — sales ops, support ops, marketing ops, data teams — who wants an agent a whole department can actually run. The core loop: define an agent with instructions, attach knowledge and tools, then run it on a schedule, on a trigger or from chat. You pick a model per agent from 20+ frontier and open-source options across OpenAI, Anthropic, Google, Mistral and DeepSeek, so a token-efficient model like Claude Sonnet can handle triage while a heavier model runs deep research. Multi-agent orchestration, native and remote MCP servers, Pods (shared workspaces with common context), Spaces (data segmentation by team) and Frames (interactive dashboards and apps) round out the build surface. A July 2026 release added self-improving skills — reusable instruction sets that encode team expertise and adapt from usage — and a May 2026 launch lets you loop any agent into an email thread by forwarding messages to it. Governance carries real weight. A dual-layer permission model separates what agents can access from who can use them, and admins get SSO via Okta, Entra ID and Jumpcloud, SCIM provisioning, audit logs, per-team data segmentation, and a choice of US or EU data residency. Dust reports 300,000+ agents deployed across 3,000+ teams, and announced a Series B to fund its next growth phase. Pricing is credit-based and seat-mixed. Free seats get 500 credits lifetime, Pro seats run 24€/seat/mo billed yearly (30€ monthly) for 8,000 credits/month, and Max seats are 120€ yearly (150€ monthly) for 40,000 credits/month. Enterprise adds unlimited connectors, pooled credits, single-tenant deployment and custom legal terms. credits reset each billing period with no rollover.
Behind the Verdict
Dust's pitch is narrower and more specific than the crowded "build an AI agent" category, and that's mostly to its credit. Instead of promising an agent that can do anything, it starts from a concrete claim: most AI tools retrieve one message from Slack or one record from a CRM, while Dust stitches context together across Slack, CRM, docs and other company systems so an agent answers with the full picture and can act on it. That framing is backed by 70+ connectors and native plus remote MCP servers, so a system Dust doesn't ship a connector for can still be reached. The build model is genuinely flexible in ways buyers should test. You choose a model per agent from 20+ across OpenAI, Anthropic, Google, Mistral and DeepSeek, and no model is locked behind a higher plan — though a higher-capability model burns more credits. Multi-agent orchestration runs on schedules and event-driven triggers, so an agent can call another agent rather than you hand-chaining prompts. Pods give shared context to people and agents in the same workspace; Spaces separate data and permissions by team; Frames turn results into interactive dashboards and apps rather than static text. Recent releases show where the product is heading. Self-improving skills, shipped July 2026, let reusable instruction sets encode team expertise and adapt from usage rather than being rewritten by hand. The May 2026 email feature loops any Dust agent into an email thread — you forward messages to it like a colleague. That matters because it meets non-technical teammates where they already work, which is the hardest part of any broad AI rollout. Governance is where Dust earns its place in a larger organization. The dual-layer permission model separates what agents can access from who can use them, with SCIM-synced groups, admin-gated overrides and zero privilege escalation. SOC 2 Type II, US or EU data residency, single-tenant deployment option, custom data retention and audit logs answer the security review questions that stall pilots. The tradeoff is that this is a platform, not a plug-in: the agent list, skills and permissions need real configuration, and someone has to own that work. Small non-technical teams with no ops owner will stall here. The credit system is the sharpest edge. A credit is Dust's unit for measuring AI usage, charged per message based on model and actions performed — search, data retrieval, code execution, actions in connected apps all consume. Basic chat with a token-efficient model costs few credits; a deep research task with multi-step orchestration costs far more. Credits reset each billing period with no rollover, Pro and Max users can continue through workspace overage if an admin enables it up to a capped amount, and Free users get prompted to upgrade. Programmatic use via API is billed at $0.01 per credit. That's manageable if you track usage in Dust and set the overage cap deliberately, and painful if you don't. It competes most directly with agent
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Real-world workflow fit
Concrete scenarios for the personas Dust actually fits — and what changes day-one when you adopt it.
Connect Zendesk and the internal knowledge base, build an agent that classifies and routes incoming tickets, and add a second agent that drafts context-aware replies for review.
Outcome: Tickets land with the right team instantly and reps start from a grounded draft, while resolved tickets get turned into reusable internal docs instead of disappearing.
Wire Salesforce and Slack into an account-research agent, run it on a trigger when a new lead enters, and let it post a briefing into the deal channel.
Outcome: Reps open a channel with the latest signal on an account already summarized, and inbound leads get scored against the live ICP before a human touches them.
Build a self-service analytics agent over connected pipelines in Spaces, then ship the results as a Frame dashboard that any teammate can query in plain English.
Outcome: Ad-hoc data questions stop queuing behind the analytics team, and campaign or pipeline rollups land as shared narratives rather than one-off exports.
Use Cases
- Automate weekly business report generation from your CRM data
- Build a support agent that answers from your knowledge base and escalates at-risk accounts
- Classify and route incoming support tickets to the right team instantly
- Brief sales reps in seconds with the latest signal on an account
- Score and route inbound leads against your live ICP
- Generate SEO-optimized blog drafts grounded in structured data sources
- Schedule daily data extraction from multiple websites and systems
- Let teammates ask data questions in plain English and get answers from connected pipelines
Models Under the Hood
as of 2026-09-21
Limitations
- Dust is a platform, not a plug-in: agents, skills and permissions need real configuration, and someone has to own that work.
- Credit consumption is variable — it depends on the model used, task complexity and any tools the agent calls, so a deep research task with multi-step orchestration draws far more than basic chat with a token-efficient model.
- Credits reset each billing period and do not roll over.
- Overage past a seat's allocation only continues if an admin has enabled workspace overage, and then only up to a capped amount.
- Programmatic API usage is billed at $0.01 per credit.
- Free seats get 500 credits for their lifetime.
- Connector limits, white-labelled Frames and single-tenant deployment sit behind the Enterprise tier.
as of 2026-09-21
Verification history
We have re-verified Dust 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
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Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Dust tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
0€
Ideal for
Occasional users, people trying Dust before committing, and teammates who only need an agent a few times a month.
What this tier adds
Starting tier: 0€ with 500 credits for the lifetime of the seat, no monthly reset.
Pro
24€/seat/mo billed yearly (30€ monthly)
Max
120€/seat/mo billed yearly (150€ monthly)
Enterprise
Custom
Ideal for
Organizations rolling AI out broadly that need single-tenant deployment, custom legal terms and volume pricing.
What this tier adds
Adds unlimited connectors and MCP servers, workspace-pooled credits, SCIM provisioning, custom data retention, white-labelled Frames, a dedicated CSM and priority support with an SLA.
Where the pricing makes sense
The company stage and team size where Dust's pricing actually pencils out — and where peers do it cheaper.
Per seat per month, Dust sits between a single-assistant subscription and a custom-built agent stack. Free seats at 0€ with 500 lifetime credits make occasional users genuinely free, Pro at 24€/seat/mo yearly (30€ monthly) suits most team members, and Max at 120€/seat/mo yearly (150€ monthly) is priced for power users running automations and deep research regularly — comfortably above $20/mo generic assistants but below assembling and maintaining your own orchestration layer. Enterprise is
Setup time & first value
How long it actually takes to get something useful out of Dust — broken out by persona, not the marketing-page minute.
For a single support or ops agent on an existing Slack workspace, expect a few hours: connect the data sources, write the agent instructions and test the routing. Getting a whole department running — separated Spaces, mixed Free/Pro/Max seats, SSO and SCIM through Okta, Entra ID or Jumpcloud — is a multi-week project with an owner. Enterprise single-tenant deployment and custom retention policies
Switching to or from Dust
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a personal AI assistant: move the repetitive prompts your team retypes into shared skills, then attach the connectors so answers come from company systems instead of pasted text.
- →From no-code automation platforms like Zapier or Make: keep the triggers, move the decision logic into a Dust agent with your knowledge attached, and use the Zapier, Make, n8n or Power Automate connectors where handoffs
- →From a custom-built agent stack: port prompts into agent instructions, expose existing tooling through native or remote MCP servers, and replace your own logging with Dust audit logs and usage analytics.
- →From a per-department chatbot: consolidate into one workspace with Spaces to keep each team's data separated, and reassign seats by actual usage.
- ↗To a custom agent framework: export your instructions and prompts, re-expose connected systems through your own MCP servers, and rebuild permissioning with your own identity provider.
- ↗To a single-assistant product: keep the handful of agents a single person uses daily and accept that shared context and cross-team orchestration have to be replaced with manual handoffs.
- ↗To a workflow automation tool: rebuild scheduled and event-driven agents as automation steps and connect the underlying systems directly, trading agent reasoning for deterministic steps.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Dust”, and we withheld 6: 6 could not be judged, because “Dust” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Dust.
Official links
Tools that pair well with Dust
Common stack mates teams adopt alongside Dust, with the specific reason each pairing earns its keep.
Inkeep
Inkeep builds AI agents for customer experience and ops teams that read your docs, CRM, and tools before they answer.
Freshservice AI
Freshservice AI puts Freddy AI copilots and agents on one ITIL-aligned ITSM, ITAM, and ITOM platform for IT teams that want faster resolutions.
Gainsight
Gainsight is a customer success platform using agentic AI to help enterprise teams retain and grow revenue.
Featured Head-to-Head Comparisons
Dust vs Truleo
These two are not competitors and no buyer should be picking between them. Truleo is vertical software for law enforcement: it connects to a department's existing RMS, CAD, LPR, BWC and jail-call systems and returns ranked case solvability scores, leads and briefings — priced per connected application plus seats, with a 60-day no-card trial. Dust is a horizontal agent platform for company ops teams that want custom agents over Slack, Notion, Salesforce and 70+ other connectors, with per-agent model choice from 20+ options. If you run a police agency, evaluate Truleo on integration coverage and data-handling policy. If you run an ops function, evaluate Dust on connectors, permissions and credit economics. Comparing them head-to-head is apples-to-oranges.
Dust vs Presto Voice
These aren't competitors — nobody shortlists both. If you're an ops, support, or data team trying to wire AI into Slack, Salesforce, and Zendesk, Dust is the only one of the two that applies. If you run drive-thrus for a QSR franchise group, Presto Voice is the only one that applies, and the Sept 21, 2026 Toast Partner Ecosystem listing is the shortest integration path if you're on Toast POS. The honest answer is that your problem, not this page, decides which one you're even evaluating.
Dust vs Locus Robotics
These are not competitors, and treating them as a head-to-head would be a category error. Dust sells software agents that sit inside Slack, Salesforce, Zendesk and 70+ other tools so ops teams can automate knowledge work. Locus Robotics sells robots and a RaaS subscription that physically move inventory across a warehouse floor. If your problem is 'our support and sales ops teams need agents wired into company systems,' Dust is the relevant evaluation. If your problem is 'our fulfillment center needs 2–3x picking productivity without rebuilding the racking,' Locus is the relevant evaluation. A buyer with both problems buys both — they don't choose between them.
Dust vs Writer
Pick Dust if your problem is wiring agents into the tools your company already runs on — Slack, GitHub, Salesforce, Zendesk — and you want per-agent model choice plus segmenting company data by team with SSO and SCIM on top. Pick Writer if your problem is getting hundreds of people to produce work that sounds like your brand and survives audit — especially in finance or healthcare — and you'll trade model flexibility for governed, brand-encoded agents on Writer's own Palmyra X6. Neither is a fit if you want a personal no-setup chatbot: both require real configuration and an owner to maintain them.
Dust vs Notable
These are not competitors, so pick by what you are. If you run ops in a non-healthcare company and need a customizable agent layered onto Slack, Drive, Salesforce and the rest, Dust is the only one of the two that fits — freemium entry, credit-based cost, 70+ connectors, per-agent model choice. If you are a health system trying to cut prior-auth backlog, denial write-offs and call volume, Notable is the specialist with the payer plumbing (Epic, Cerner, athenahealth, Twilio) Dust simply does not have. Nobody should be comparing these side by side; they solve different problems for different buyers.
Dust vs Genspark
Pick Dust if agents need to act inside your company's real systems — Slack, Salesforce, Zendesk, GitHub — and you have an ops owner who will configure permissions, Spaces and SSO. Pick Genspark if the job is know-how work: cited research, decks, docs, podcasts and no-code internal tools, ideally on Google Workspace or Microsoft 365. If you cannot name the systems the agent must touch, Dust's setup cost is wasted and Genspark is the faster win.
Dust vs Cryptohopper
These aren't competitors, so there's no head-to-head pick to make. Dust is for ops, support, sales, and data teams that want agents wired into Slack, Notion, Salesforce, or Zendesk with per-team data segmentation, SSO/SCIM, and audit logs — and it's freemium with consumption-based credits that don't roll over. Cryptohopper is a paid crypto trading bot: Explorer starts at $24.16/mo after a 3-day trial, and you're buying Copy Bot, DCA, trailing orders, backtesting, and a no-code Strategy Designer across exchanges like Binance and Kraken. Buy Dust to deploy multiplayer AI inside your company; buy Cryptohopper to automate crypto trades.
Dust vs Toolhouse
These are not the same product wearing two logos. Dust is infrastructure for teams who want to build, govern and segment their own agents — per-agent model choice, SSO/SCIM, Spaces to wall off data by department, and MCP as an escape hatch for anything the 70+ connectors miss. Toolhouse is delegation: you brief a worker by email or chat, it runs 24/7 and hands back a deliverable, across 1,000+ integrations. If you have an ops owner and compliance questions, Dust. If you have non-technical staff drowning in repetitive email, data and admin work and $500+/month is acceptable, Toolhouse. The hidden cost on Dust is credits that vary by model and tool use and don't roll over; the hidden cost on Toolhouse is the paywall itself.
Dust vs Air Ai
These are not competitors — this is not a head-to-head anyone should run. If you're a commercial ops, support, or engineering team that wants to build agents on top of Slack, Notion, Salesforce, and GitHub with per-team data segmentation and SSO, Dust is the relevant product and Air is simply out of scope. Air is for military commands, acquisition and sustainment offices, and defense program teams with a readiness mission and existing enterprise systems to feed its Readiness Graph; it's sold through a vendor-led deployment, with no published price and no self-serve path. No buyer with one budget and one problem shortlists both. Choose based on which world you're in, not on feature-by-feature scoring.
Alternatives to Dust
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Inkeep builds AI agents for customer experience and ops teams that read your docs, CRM, and tools before they answer.
Freshservice AI
Freshservice AI puts Freddy AI copilots and agents on one ITIL-aligned ITSM, ITAM, and ITOM platform for IT teams that want faster resolutions.
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