Platform
One version of the truth, for your people and your AI.
Daitonomy brings every system together into one living picture of the business. The same product, customer and order is recognised everywhere, and every number shows where it came from. Your teams, your dashboards and your AI agents all work from that one picture.
Your data, structured
Any data in. One model. Better data back out.
Your ERP, accounting, HR, webshop and marketing tools were never designed to talk to each other. Daitonomy takes in data from all of them, whatever its shape, organises it into one model of your business, links it together, completes what is missing, and sends it back to the systems where your teams work.
Common systems connect out of the box. Anything else is mapped into the model within two weeks.
One model of how your business actually works
Linked across systems, for example
Ad campaign → Order → Product → Supplier invoice → Real margin
Questions that used to need four exports and a spreadsheet become one question.
- Webshop & marketplaces — complete, consistent product content
- Ad platforms — richer feeds and real margin to bid on
- ERP & accounting — clean product records and consistent categories
- Your own tools & AI — one structured source through API
Your existing systems perform better, without replacing a single one of them.
Data audit
We find what is wrong in your data, before it costs you.
Because every system is linked in one model, errors that are invisible inside a single system become obvious. Daitonomy checks continuously and flags each issue with what it affects, so it can be fixed at the source.
Outcome: decisions made on numbers you can trust, instead of on errors nobody noticed.
| What we find | What it costs you |
|---|---|
| Wrong or missing cost prices (COGS) | Margin, pricing and ad decisions built on the wrong number |
| Products selling below cost | Every extra sale loses money |
| Products in the wrong lifecycle stage | New items not pushed, declining items still bought in |
| Phased-out products still advertised or reordered | Budget and cash spent on what you want to stop selling |
| Stock that has stopped moving | Cash locked in the warehouse, losing value |
| Prices or stock that differ between systems | Overselling, wrong prices in one channel |
| Duplicates and missing attributes | Products rejected by channels or impossible to find |
Product enrichment
From a code in a spreadsheet to a product that sells.
Most product data arrives thin: a supplier code, a short name, a price. Daitonomy finds the missing facts from manufacturer sources, writes clear content, fills every attribute your channels ask for, and marks what was found, what was calculated and what was written.
TRN GTX 42 BLK
- Description missing
- Category missing
- Material, fit, specs missing
- Barcode present
- Price present
Hard to find in search, rejected by some channels, invisible to AI shopping assistants.
Trail Runner GTX Men’s Waterproof Trail Shoe, Black, EU 42
- Description written · checked against source
- Category Footwear › Trail running
- Material, fit, specs from manufacturer
- Barcode verified
- Price verified
Outcome: found in search, accepted by every channel, understood by AI shopping assistants, and published everywhere at once.
Illustrative example
Enrichment
Enrichment for every kind of data, not only products.
Raw data from one system tells you what happened. Linked and enriched, it tells you why, and what to do next. The same method that completes a product record completes your customer, marketing, stock and demand data.
Products that sell themselves
We add- Titles, descriptions and FAQs, checked against the source
- Categories and every attribute your channels require
- What it is for, who it suits and when it is the wrong choice
- Translations for every market
So you can: get found in search, pass every channel’s checks and be understood by AI shopping assistants.
Customers understood by behaviour, not by name
We add- New versus returning customers over time
- What is bought together, and what is left in the cart
- Which channel brought each order
- Segments built on buying patterns, without personal details
So you can: keep the customers worth keeping, and market to patterns instead of guesses.
Every euro of spend linked to real profit
We add- Ad, email and search performance tied to the products sold
- Spend against attributed revenue, per channel and month
- Profit on ad spend, not just return on it
- Organic search performance per product page
So you can: move budget to what actually earns, across every channel at once.
Every product classified by what it does for the business
We add- Real margin, after costs and returns
- Sales speed and return on stock held
- Classes: heroes, steady sellers, cash drains, seasonal
- Stock and demand across every location
So you can: buy, price and promote with the whole picture, not one system’s view.
What customers ask, linked to what you sell
We add- What visitors type into your site search, and what they don’t find
- Questions asked to your product advisor, per product
- Support tickets and calls, grouped into themes
- Gaps between what is asked for and what you offer
So you can: fix the range, the content and the service where demand is going unmet.
All of it, linked
- One enriched record per product, customer segment, campaign and location.
- Every enriched value shows where it came from and how certain it is, and is sent back into your webshop, ad platforms, ERP and your own tools.
- People data is handled at the level of roles, teams and costs, never personal details.
Business rules
Your business rules, built in
Your way of doing business, applied to every decision.
Every company runs on rules: how you price, which suppliers come first, what stock you keep, what you will and won’t say. Today most of them live in people’s heads and in spreadsheets. In Daitonomy they become part of the system, so every report, every enrichment, every agent and every workflow follows them, automatically.
Lower the price of Trail Runner GTX
€149.00 → €129.90
- Margin stays above 25%, after costs and returns
- Not below the supplier’s minimum advertised price
- Price ends in ,90
- Discount is 12.8%, above the 10% limit: sent to the category manager for approval
The agent did the work. Your rules decided what happens next, and the record shows which rule applied.
The rules you can build in
Pricing
How you price- “Never sell below a 25% margin.”
- “Follow the supplier’s recommended price where one exists.”
- “Round to prices ending in ,90.”
Suppliers
How you buy- “Order from the preferred supplier first, then the backup.”
- “Respect minimum order quantities and lead times.”
- “The manufacturer’s data wins over the reseller’s.”
Stock
What you keep- “Keep two weeks of safety stock on best sellers.”
- “No reorders on products being phased out.”
- “Move stock between locations before buying more.”
Marketing
Where money goes- “No ad spend on products that are out of stock.”
- “Only advertise products that clear the margin target.”
- “Never exceed the monthly budget per channel.”
Content & brand
How you speak- “Use our tone of voice and terminology.”
- “No health or performance claims we cannot prove.”
- “Every product in this category must list its size and material.”
Approvals
Who decides- “Price changes above 10% need the category manager.”
- “Purchase orders above a set amount need finance.”
- “Anything new to the range is checked by a person.”
Written once
Your best people’s know-how becomes a company asset that doesn’t leave when they do.
Applied everywhere
The same rules hold in every channel, every market and every agent. No exceptions by accident.
Explained every time
Every decision shows which rule it followed, so you can check it, and change the rule when the business changes.
Build or buy
Keep building your own tools. We keep the data right.
Build the AI you want. Don’t rebuild the foundation. Daitonomy doesn’t replace your AI ambitions. It gives them something solid to stand on, so your team spends its time on what makes you different.
Building a tool on your systems’ APIs takes an afternoon. Keeping it right takes forever.
Each tool connects on its own
- Margin report — 5 connections
- Ad optimiser — 5 connections
- Stock planner — 5 connections
- AI assistant — 5 connections
20 connections to build, secure and repair
Tools built on Daitonomy
- Each source connected once
- Every tool reads one source
- Margin and stock defined once
- Maintenance our job
5 connections, maintained by our team
| Aspect | AI on your own data stack | AI on Daitonomy |
|---|---|---|
| Getting to a trusted answer | Months of connecting and cleaning data before the first reliable result. | Standard systems connected at onboarding; other systems mapped in two weeks. |
| Keeping data clean | Your team, forever, every time a system changes. | Checked and corrected continuously, as part of the service. |
| Explaining a decision | Hard to say which data the AI used, or how reliable it was. | Every number shows its source and how certain it is. |
| Letting agents act | Too risky, so the AI stays a reporting tool. | Safe to act, because every action traces back to trusted data. |
| Connections | Every tool connects to every source it needs. | Each source connected once, for every tool. |
| When a source changes or breaks | Noticed when someone complains; fixed when the builder has time. | Our monitoring detects it; our team fixes it and tells you. |
| Who understands the logic | The builder, and their chat history with the AI. | Written definitions, and engineers who know the system. |
| History | Overwritten whenever a price or cost changes. | Kept, so last quarter’s numbers stay last quarter’s numbers. |
| Following your business rules | Rebuilt in every tool and prompt, and quietly broken when one is missed. | Defined once, applied to every report, agent and workflow. |
| Automating the next process | A new project, new integrations, new risk, every time. | A new workflow on the same foundation, with the same agents and the same trusted data. |
| Where your data lives | Wherever each tool and provider happens to put it. | In Europe, on dedicated infrastructure. |
| What your team works on | Plumbing. | The ideas that set you apart. |
We take care of
Monitoring
We check every source is fresh and complete, and act when it isn’t.
Correct data
We check the numbers against the source systems and define margin, revenue and stock once, in writing.
Outages
We detect it, tell you what is affected, fix it and confirm when the data is right again.
Platform changes
We keep up with every API change, so your tools don’t have to.
Bugs
Our engineers fix what breaks, also when someone on your team is away.
New requests
A new source, field, metric or market is something you ask for, not something you build.
Access
Connections and credentials in one place, with access per person.
Before you let AI run your business, make sure it knows your business.
Bring us one question your systems can't answer today. We'll show you what the answer looks like when all your data finally agrees.