Data analytics handoffs
Ask for the answer, not the dashboard ticket. Anton plans, queries, cleans, charts, and explains.
Agent
The open-source AI coworker.
Anton turns plain-language requests into finished deliverables — dashboards, reports, cleaned spreadsheets, research packs, and workflows. On MindsHub it runs with the data, tools, and operational backbone it needs to actually finish the work.
Anton is a different shape of agent. You don’t prompt it; you hand it an outcome. "Pull this week’s revenue, explain the biggest movers, and ship a dashboard" returns a published dashboard, a written explanation, and a scratchpad with every SQL query and Python step it used to get there.
On MindsHub, Anton runs with direct connections to your databases, warehouses, and SaaS tools — plus a transparent scratchpad, persistent memory, and a Model Router so it can pick the right model per step. The result is a coworker that finishes deliverables, not a chatbot that drafts them.
Ask for the answer, not the dashboard ticket. Anton plans, queries, cleans, charts, and explains.
Weekly operating reports, monthly financial packs, board prep — Anton runs the same shape of work each cycle.
Contracts, invoices, expenses — Anton compares against rules, extracts exceptions, and prepares a review checklist.
Combine calls, tickets, CRM notes, and product issues into one ranked, sourced view.
Source-backed briefs, market sizing, content repurposing, vendor comparisons — all shippable, not just draftable.
The full set of 36 use cases lives at /use-cases — ops, data, GTM, product, finance, legal, people, research, content.
Anton is open-source either way. The difference is the operational backbone around it.
| What you handle… | Self-hosted | On MindsHub |
|---|---|---|
| Secrets management | You manage keys, rotation, scoping | Built-in credentials vault |
| Model access | One provider relationship per LLM | Model Router with `latest:*` aliases |
| Persistent execution | Queues, workers, retries you build | Managed runtime, jobs survive restarts |
| Memory across runs | Your storage, your schema, your reset logic | Shared memory store, built in |
| Tool integrations | Per-tool plumbing, per-tool auth | Pre-built catalog, shared auth |
| Observability | You wire your own traces | Scratchpad + audit log on every run |
| Scaling | VMs, queues, autoscaling rules | Managed — no servers to mind |
Anton needs real access to databases, warehouses, and SaaS tools to finish work. MindsHub provides the connection layer with proper auth scoping.
Every SQL query, Python cell, intermediate table, chart attempt — visible, auditable, replayable. The opposite of a black box.
Yesterday's analysis informs today's. The schema decisions Anton made last week don’t need re-explaining.
Reasoning for the plan, vision for the chart-reading, fast drafts for the summary. Anton picks the right model per step through the Router.
Long-running analyses survive restarts. Scheduled runs land on time. Failures surface where you can see them, not silently.
No queues, no VMs, no orchestration scripts to maintain. Same Anton you can run locally — on the operational stack you'd otherwise build.
Point Anton at the systems where the truth lives — Postgres, Snowflake, BigQuery, Notion, Slack, Linear, your file storage.
Plain English: "Build this dashboard." "Produce this report." "Review these contracts." No prompt engineering required.
A finished deliverable plus a visible trace of how it got there. Edit, ship, or fork the run to refine it next time.
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