Software that finishes the task.
An agent does more than answer a question. It plans a few steps, uses your tools, and completes the work, with a person approving anything that matters.
A chatbot talks. An agent acts. Give it access to your inbox, calendar, CRM and spreadsheets, define what it may do on its own and what needs a yes from you, and it works through a task from start to finish: research the lead, draft the reply, book the meeting, log the result.
Agents connect to your tools through function calls and, increasingly, through the Model Context Protocol, an open standard Anthropic introduced in late 2024 and later donated to the Linux Foundation's Agentic AI Foundation. Standard connections mean your automations are not tied to one AI vendor.
What teams are automating right now
Lead research and qualification
An agent looks up a new inquiry, checks the company, scores fit against your criteria and drafts a first reply for a person to send.
Inbox triage and drafted replies
Messages are sorted by type and urgency, routine ones get a draft in your voice, and anything sensitive waits for a person.
Scheduling and rescheduling
Requests are matched against real availability and booking rules, then confirmed, reminded and followed up automatically.
Reports that assemble themselves
Numbers from three systems become a weekly summary with the exceptions highlighted, instead of an hour of copy-paste.
Content repurposing
A webinar or long article becomes posts, an email, an FAQ entry and talking points, each in a draft that a person approves.
Document intake
Invoices, forms and emails are read into structured records, and anything the agent is unsure about is flagged.
What you get
- A written map of the workflow as it runs today, with the time it costs
- An agent with defined tools, permissions and spending or action limits
- Human approval steps placed where a mistake would be expensive
- An audit log of every action, and alerts when something looks off
- An evaluation set of real cases, so model updates are tested before they reach you
- Documentation and a hand-off so your team can run and adjust it
A typical engagement
- Pick one workflowSomething repetitive with a clear start and finish, and a person who owns it.
- Watch it done by handWe shadow the current process, including the odd cases people handle without thinking.
- Prototype in suggest modeThe agent prepares work and a person approves it, so trust is earned with real results.
- Widen the autonomyWhere error rates stay low, approvals relax. Where they do not, they stay.
A good fit if
- The work spans two or more tools and follows a repeatable pattern
- The volume is high enough that saved time adds up
- Someone on your team owns the process and can judge the output
Probably not a fit if
- The process changes every day and nobody could write it down
- A wrong action would be costly and no one can review it first
- You want a fully unsupervised AI employee
Common questions
Will it make mistakes?
Sometimes, yes. Models are not perfect, so we design for that: approvals on consequential steps, hard limits on what it can do, a full log, and a test set we re-run when anything changes.
Which tools can it connect to?
Anything with an API or a reliable export. Common examples are Google Workspace, Microsoft 365, HubSpot, Salesforce, QuickBooks and calendars. For older systems with no API, computer-use models can work as a slower fallback.
What happens when the AI models change?
They change constantly. Because we keep an evaluation set, we can test a new model against your real cases before switching, and switch back if it does worse.
Who sees my data?
We tell you exactly which providers touch which data, choose providers whose terms keep your data out of model training, and log access. Details go into your agreement.
Works well with
Knowledge systems
Ask questions of your own documents, policies and data and get answers with sources. Private and always current.
Learn more 05Readiness checks
A hard look at your data, tools and security, so the AI you add stands on solid ground.
Learn more 06Training and pilots
Hands-on sessions for owners and teams, plus small pilots that prove the value before you commit to more.
Learn moreWant help with agents and automation?
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