AI Employees & Managed Automation
An AI employee that knows your business and improves every week. We build it, run it, and fix it before you notice. You don't touch tokens, models, or infrastructure.
We build and run managed AI employees for businesses that don't want to manage AI themselves. Each one is shaped to your operations, integrates with the tools you already use, and gets better the longer it runs. You get predictable monthly pricing, async Loom updates, and a watchdog that catches breakage before you do. No token bills, no model decisions, no infrastructure to manage. Just the work getting done.
Why it matters
01
Reclaim 15+ hours per employee per week on the highest-ROI workflows
02
Predictable monthly cost with no token bills or scope creep
03
Monitored and fixed continuously. We know before you do
04
Improves every week as we tune it to your real operations
05
Scale operations without scaling headcount
06
No technical lift from your team. We handle the integrations, the model, the hosting
What you get
01
Discovery and workflow audit (week 1, free)
02
Custom AI employee built and deployed for your operations
03
Integrations with the tools your team already uses
04
Continuous monitoring, watchdog, and async Loom updates
05
Weekly tuning and improvements based on real outcomes
06
Monthly outcome review and roadmap
07
Customer-facing kanban for requests and visibility
08
Everything included. No token bills, no scope creep math
How to judge fit
The service should make repeat work feel smaller fast.
A good automation engagement usually creates visible time savings, fewer manual touchpoints, and clearer ownership of the workflow.
- Repetitive tasks can be standardized
- The workflow crosses tools, people, or inboxes
- The team already feels the cost of delay
How we deliver
01
Discover
We audit your workflows and find where automation saves the most time and money
02
Design
We map out exactly what gets automated, what tools to use, and what results to expect
03
Build
We build, test, and deploy your automated workflows -- typically live within 4-8 weeks
04
Optimize
We monitor performance, fine-tune, and expand what's working to new use cases
Proof, not promises
See it in action
Legal services · Managed AI Employee engagement
12-person mid-size law firm
A 12-person mid-size law firm was losing associate and paralegal hours to first-pass intake: opening every new enquiry, reading the attached documents, running conflict checks, and triaging urgency.
Why this proof matters here: Best for teams losing time to repetitive internal work, slow follow-up, reporting drag, or messy tool handoffs.
01
-70%. Intake processing time
Time from new enquiry to triaged matter file dropped by 70% on the firm's highest-volume practice area. Measured against the firm's own baseline, not an industry average.
02
1 week. Time to first workflow
First intake workflow was live inside the first week of the engagement, on a private workspace integrated with the case management and email tools the team already uses.
03
6 weeks. Time to full system
Full intake pipeline in production within 6 weeks of kickoff, with the watchdog running and the customer-facing kanban live.
04
11 weeks. Payback
Engagement paid for itself inside 11 weeks, measured against the team's prior intake cost. The number is conservative: the firm has not yet counted the cost of the next hire it was able to make.
05
1 new associate. Capacity added
Firm hired a new associate within two quarters of go-live, funded by the freed paralegal and associate hours. The AI employee did not replace anyone. It made the next hire possible.
Helpful next step
Pressure-test the savings first
Use the automation savings calculator to turn a vague workflow problem into a rough time and cost estimate before we scope anything.
Tools we use
We choose tools for maintainability, delivery speed, and team handoff, not for stack theater.
Common questions
We're a small team -- is automation worth it for us?
Small teams benefit the most. Automation multiplies what each person can do. We focus on high-ROI implementations -- things like automating repetitive admin work, streamlining customer communication, or generating reports automatically -- that pay for themselves quickly.
Do we need our own data or special infrastructure?
Not at all. Most automation works with your existing tools and data. We connect what you already use and make it work smarter. If you have proprietary data that could make things even more powerful, we can build custom knowledge bases around it.
How long does it take to see results?
Most automation workflows are live within 4-8 weeks. We start with a free discovery call to identify your highest-impact opportunities, then prototype fast so you can see real results before committing to a full build.