AI didn't remove your bottleneck.
It made you the bottleneck.
Someone runs the agents all day and re-pastes the context every time they switch chats or tools. Give every client and every project its own AI project manager instead. It holds the context, runs the agents, and connects to your stack.
Built for agencies
Also for PE portfolios and founders still doing marketing themselves.
- Same AI project manager, every company
- No new headcount to manage
- It holds the context so nobody re-pastes it
- It runs the agents all day, you do not
- It connects to the tools you already use
- A human stays in control
- It runs the agents for you
- It connects to your tools in hours
What your AI project manager runs
One offer. Many jobs. Pick the one that hurts most today.
Outcome first. System second. Workers last.
Start with the job closest to revenue. Measure it. Add another worker when the numbers make sense.
Everything you need to decide, in one place.
Your agents work. Someone still has to run them.
The AI project manager takes that job. It holds the context, runs the agents, and reports back.
Start with the free Teardown on one client account.
Find the path that fits where you are.
These are different scopes of work, not one product ladder. Pick the route that matches what you need today.
Get personalized guidance. Tell Sam what you want to grow and get a recommended path in seconds.
A written map of the jobs closest to revenue, so you know where to focus first.
Pick the packaged system that delivers it. Then choose how to run it: self-run, AGL-installed, or AGL-managed.
AGL operates the connected revenue engine for you, ongoing. A different scope than a single system.
Apply the same systems across teams, regions, or the portfolio.
See a day in your business. You vs AI workers.
Tell Sam what you want to grow. He'll show you the opportunity, the strategy, and the system that moves it.
Start With the Job That Hurts Most Today.
Your AI project manager runs one job first. Add jobs when the first one works.
- Large initial engagement
- Multiple services at once
- Multiple initiatives
- Multiple KPIs
- More difficult to isolate which job created value
- Higher initial commitment
- Start with one growth outcome
- Set the strategy that moves it
- Execute with the right systems, people, and AI
- Track the KPI it moves
- Measure the economics
- Add another worker when it makes sense
Start With the Constraint. Earn the Right to Expand.
AGL doesn't require you to deploy an entire AI workforce on day one. Start with the job that matters now and expand based on measurable business value.
It Connects to the Stack You Already Use.
Keep your CRM, email, and sales tools. The AI project manager plugs into them and runs the work there.
Beta means live for early customers. Custom means scoped as an AGL Installation add-on. Anything outside this list gets reviewed before we commit to it.
Built From Systems That Already Produced Results.
We hit this wall in our own agency first. One person stuck running the agents and re-pasting context all day. So we built an AI project manager for each client, trained on $17M+ in client revenue generated.
More agents did not fix it. They made it worse. Every new agent is one more thing to brief and babysit. The fix is not more agents. It is one AI project manager per client that holds the context, runs the agents, and keeps a human in control.
Operating experience and client outcomes from the marketing and sales systems AGL built and ran.
Outcomes produced by one individual worker. Separate from the operating experience above.
The AI project manager and its workers were trained on the systems behind $17M+ in client revenue generated.
Targeting, outreach, lifecycle and reporting connected into one visible sales system.
CAC reduced from $500 to $50 through better buyer selection, research and follow-up.
Independent reviews on Upwork that AGL cannot edit or remove.
Verify on Upwork →Top-rated profile with completed fixed-price work and ongoing client relationships.
Verify on Upwork →Experience across companies with different buyers, markets, teams and maturity levels.
Operator experience connecting growth, repeatability and enterprise value.
From $0 to $1.2M in qualified pipeline
Targeting, outreach, lifecycle and reporting were connected into one visible sales system.
Customer acquisition cost reduced from $500 to $50
Better buyer selection, prospect research and follow-up brought in more of the right customers, and the acquisition economics improved without a larger SDR team.
Know what kind of proof you are looking at.
Outcome produced with an AGL client and connected to work AGL performed.
Third-party review on Upwork that AGL cannot edit or remove.
Experience from operator roles across companies and deals prior to and alongside AGL.
Industry data or research from independent sources, not AGL results.
Also for larger teams: one AI project manager per client, across every team.
Same offer, wider scope. It holds the context, runs the agents, and a human stays in control.
Run the same chain inside each company, then compare it across them. Sustainable growth is not only revenue, it is repeatability, visible economics, operating leverage, lower key-person dependency and measurable execution.
Start self-service. Browse the catalog, deploy one worker, and measure the economics before adding more.
Browse AI WorkersSkip the catalog. Tell AGL where growth is stuck and we'll scope the workers, integrations, and managed operation around your business.
Talk to AGLOne AI Project Manager Per Client.
It holds the context, runs the agents, and connects to your stack. Start with the free Teardown.
Not sure where growth is getting stuck? Ask Sam What Fits →
