AI products and engineering
Build AI into the work your business runs on.
DDYCorp builds and runs AI systems around the records, documents and tools your teams already use.
Where DDYCorp helps
Today
Matched line by line before every close.
DDYCorp builds
Invoice-to-order matching with an exceptions queue
Result
- INV-2231Price differs from order
- INV-2247No matching order
- 409 invoicesMatched and ready
What DDYCorp does
One team, from scattered data to decisions.
We handle the whole path: bringing the information together, the analytics and AI workflow built on it, and the operation that turns insight into action.
Connect your information.
Records, documents and data from different systems, brought into one place and checked.
Analyze it, then act on it.
Analytics that show what matters, and workflows that carry each insight into the work, with review where it matters.
Keep it running.
Monitoring, fixes and changes after launch, with a named owner.
How it looks in practice
Start with a task your team repeats.
A weekly operating review, for example. We turn it into a system that gathers the inputs, checks them and drafts the report, so your team only reviews what needs judgment.
- 01
Inputs
Business records, the period report, and supporting documents
- 02
Preparation
Match fields across sources and flag what is missing
- 03
Review
A person checks exceptions and signs off conclusions
- 04
Output
A draft report with sources linked and follow-up items listed
Products
Products built around information and action.
- 01
VectorOpus
In developmentFrom scattered data to decisions your business acts on.
We're developing VectorOpus to bring data from many sources into one place, prepare and analyze it, and turn the insight into action: a decision, a review, a task for the right person. The aim is to keep the prepared data and methods, so each cycle builds on the last instead of starting over.Explore VectorOpus - 02
StreamGuard
Early developmentCamera evidence for operational review.
We're developing StreamGuard to make recorded camera activity easier to search and review. The direction: findings backed by the relevant footage, and supported events connected to the follow-up work they need.Explore StreamGuard
Services
Engineering around the work you need done.
- 01
Data and content engineering
Connect, clean, or move the information a task depends on. For example, moving content off an aging document platform without losing its metadata, or joining finance and operations records that never quite match. - 02
AI workflow implementation
Turn one recurring task into a workflow that runs on your systems, with a person reviewing where judgment matters and results checked against examples you agree. - 03
Managed operation
Look after agreed applications and workflows after launch: monitoring, fixes when a source changes, and regular reviews of quality and running cost.
How we work
Define the result. Build it. Put it to use.
Step 01
Agree the task.
Choose one recurring task. Agree who owns it, how it is done today, and what a good result looks like.
Step 02
Work with real examples.
Use a representative set of your records and documents to confirm access, integrations, review steps, and where it will run.
Step 03
Test before scaling.
Check results, exceptions, review effort, and running cost against the criteria agreed in step one. Adjust before rolling out.
Step 04
Decide who runs it.
Hand over to your team with documentation, or have DDYCorp operate it under an agreed scope. Either way, ownership is written down.
Product thinking. Enterprise engineering.
DDYCorp combines product development with experience in enterprise content, application integration, and technical delivery. So we build around the systems and processes you already run, rather than asking you to replace them.
- We build around the systems and data you already have.
- A person reviews wherever judgment matters.
- Results are tested against agreed examples before anything scales.
- Ownership after launch is agreed and written down.
Next step