CRM
Mail
Calls
Chat
The knowledge is there, but scattered.
What a client wants is in the CRM, in emails, in calls and in one person's head. Whoever needs something searches and asks around.
For small digital service teams
A chatbot becomes an employee: AI that works on its own and grows your company.
A chatbot doesn't know your clients, proposals and conversations, and it waits until you ask. With your own data foundation, you get AI agents that work with it on their own: answering inquiries, preparing proposals, following up until the deal is signed. All of it runs in your own accounts and belongs to you.
Sound familiar?
The knowledge that brings more revenue is already in your company. Nobody can get to it fast enough.
If any of these sounds familiar, it's worth a conversation.
Write the follow-up to our client Berger.
Hi [Name], thank you for the nice conversation. As discussed, I am sending you [proposal] for [project].
0 sources · doesn't know you
So far, AI hasn't done much for you.
ChatGPT doesn't know your clients, projects or templates. What comes out is generic text that someone has to rewrite first.
open3
People do work the computer should be doing.
Copying notes, retyping data, chasing status updates. That time is missing for clients and new deals.
The data layer
Your tools hold the knowledge, and the data layer brings it together.
Your data layer collects what happens in your CRM, inboxes, calls and documents, and sorts it by clients, conversations and knowledge. Your agents work on top of it, and anyone on your team can ask questions and get an answer with its source.
Your tools
CRM3 deals without update
Email12 emails unassigned
Phone2 calls without notes
CalendarMeeting unprepared
Documents5 versions in circulation
Chat7 open threads
$ status --live
clients_deals1240○ empty
calls_mails3870○ empty
knowledge_docs470○ empty
AI agentreads from the data layer
Ask your data …
Your team
Sales
Delivery
Management
What you get
Routine work runs on its own. Your team has a clear head for conversations and decisions.
Everyone on the team becomes a bit of a manager: spotting problems, handing out tasks, checking results. The agents work through the tasks.
01 · Routine
Routine work runs on its own.
Transferring notes, updating the CRM, collecting status, following up: done before anyone asks.
02 · People
People talk more to people and less to software.
While the agent prepares proposals and follows up in the background, your team is talking to people: with the client, in the project, within the team.
03 · Leadership
Everyone on the team becomes a bit of a manager.
Spot a problem, hand it to the agent as a task, check the result. The agent does the work itself.
Your path
This is how you get a system that works for you.
Find out what's possible.
You show us how your team works, where valuable knowledge sits and which tasks are left undone because they took too much effort until now. From that you get a concrete plan for how data and AI move your company forward, even where you don't see a solution yet.
ResultYour plan, sorted by impact
PlanAgents
Lever 1Revenue23
Lever 2Time9
Lever 3Revenue4
+Next idea
data layer
clients_deals
calls_mails
knowledge_docs
$ sync
01
02
03
Your company gains new capabilities.
You get the data foundation and the AI systems that work with it. Your company's knowledge becomes usable. Agents take on demanding tasks across several systems. Your team can ask questions, prepare decisions and get done the work there was never enough time, visibility or capacity for.
ResultData layer and first agents, in your accounts
PlanAgents
Lever 1Revenue23
Lever 2Time9
Lever 3Revenue4
+Next idea
data layer
clients_deals
calls_mails
knowledge_docs
$ sync
01
02
03
Grow with what becomes possible.
Once the foundation is in place, more becomes possible. Your system keeps growing, takes on new tasks and brings new AI capabilities into your working day. What still takes a lot of manual work today simply works tomorrow. Your company learns to use these possibilities for itself.
ResultMore work your system takes over, every month
PlanAgents
Lever 1Revenue23
Lever 2Time9
Lever 3Revenue4
+Next idea
data layer
clients_deals
calls_mails
knowledge_docs
$ sync
01
02
03
PlanAgents
Lever 1Revenue23
Lever 2Time9
Lever 3Revenue4
+Next idea
data layer
clients_deals
calls_mails
knowledge_docs
$ sync
01
02
03
Discovery Call
Let's talk about your company.
Tell me where things get stuck, even if you don't know yet how AI can help. In the Discovery Call we look at it together, and I'll tell you honestly whether an audit is worth it.