Ontology · Agentic Workflow · AX
ModivLab gives your company's data a semantic structure and automates office work with AI agents that operate on it. We don't resell off-the-shelf software. We go on site and build what fits your business.
Why
01
No one has ever defined what “account”, “due date” or “approval” mean in your company. AI without context gives plausible but wrong answers.
02
The same information lives under different names in spreadsheets, the ERP, messengers and email. Automation breaks down on disconnected data.
03
Adding a chatbot doesn't change how work flows. Agents have to actually take over the judgments and handoffs people used to make.
Approach
Most AI projects start by bolting on a chatbot. We reverse the order: define your company's concepts and relationships first, then build agents on top.
We define the things your business works with (customers, orders, documents, people) and how they relate, weaving scattered data into one map. It's how AI learns what connects to what.
We design AI agents per task that read the structure and make decisions. They look things up, organize, draft, and hand off to the next person.
We connect agents to the email, messengers, documents and internal systems you already use, so they run as one workflow. People focus on reviewing and deciding.
Services
Our engineers embed with your team, Forward Deployed Engineering style, observe how work actually happens, then design and build the agentic workflow that fits. We build to the work instead of bending the work to a product.
We start AI transformation (AX) with the office work that eats the most time: writing reports, gathering data, reviewing documents, answering repeat requests. We measure success in hours actually saved.
We build a knowledge model that structures scattered data into business concepts and relationships. It decides whether AI adoption succeeds, and it stays reusable for every automation you add later.
Case
An integrated business system that our founder is designing and building first-hand at the SME where they currently work. It brings scattered internal systems into one ERP, with AI working alongside staff on top of it.
01→
Handle customer requests and find new sales opportunities in each conversation.
02→
Confirmed deals go straight to the installation team, with the full sales context.
03→
The installation team schedules jobs and talks to customers directly.
04
After-sales service and inquiries are handled from a single screen.
01
First we map which process moves from which team to which, and turn the company's whole workflow into one structure. The sales-to-customer-care flow above is that backbone.
02
The detailed tasks people do at each stage move into the system one by one, matched to how the company really works. Everything runs in one system and one context, so the next person and the AI pick up exactly where the last step left off.
03
When staff talk with the AI agent, it works out which screen needs which feature or integration and files a development ticket. Tickets are built in short cycles and shipped right away. The system keeps growing from the requests of the people who use it.
Process
STEP 1
Review workflows and data to find where automation pays off most.
STEP 2
Decide the ontology, agent structure and where people stay in the loop.
STEP 3
Start with a small scope on real work, run it, and refine on results.
STEP 4
Transfer how to operate it so your team keeps using and improving it.
Small and mid-sized companies without a dedicated AI team that want to spend less time on repetitive work. Teams that would rather see one team's workload shrink now than launch a grand transformation program.
Contact
Tell us the one task that takes up most of your time. We'll tell you whether it can be automated and where to start.
[email protected]