Solution · 03
AI-Ready Business Data
Create one trusted data base for reporting, automation and AI.
The problem
Why this exists
Systems do not line up, teams use different numbers for the same measure, and reports depend on manual spreadsheet work.
- Systems hold different versions of the same information.
- Teams argue about which number is correct.
- Reports take days to prepare.
- AI and automation projects stall on data quality.
What it does
- Connections to approved business systems
- Cleaned, standardized business data
- Agreed KPI definitions with owners
- Dashboards, reports and reusable data for AI
How it works
The steps we run
- 01
Map systems, reports and decisions
- 02
Connect the approved sources
- 03
Clean the data and agree KPI definitions
- 04
Build dashboards and reusable data
- 05
Monitor quality, usage and cost
Use the right data product
AI-ready business data vs AI training data
Both need structure and quality control, but they serve different jobs. AI-ready business data supports operational assistants, automation and analytics over current business information. AI training data consists of curated examples used to train, tune or evaluate models.
| Approach | Best for | Customer operates infrastructure? | Data delivered ready for use? | Ongoing maintenance |
|---|---|---|---|---|
| AI-ready business data | Operational AI, assistants and analytics | Usually ERP, CRM, documents and approved business systems | Consistency, context, structure and definitions | Business data and AI product teams |
| AI training data | Training, fine-tuning or evaluating models | Curated examples and datasets | Labels, examples, splits and evaluation criteria | ML, LLM and data operations teams |
Services combined
Built from our core capabilities
Measures of value
How we measure success
Lead industries
Where it fits best
See what ai-ready business data would look like for you
Tell us the problem, the systems and the target. We come back within one business day with scope, first result and timing.
Other solutions
01
Web & Market Data Monitoring
Know when important prices, products, suppliers, sellers or rules change.
02
Model-Ready AI Training Data
Give your ML and LLM team clean, labeled and reliable data.
04
Document Processing Automation
Process invoices, orders, contracts and forms with less typing.
05
Company Knowledge Assistant
Help employees find reliable answers from company documents.
FAQ
AI-Ready Business Data questions, answered
How this solution scopes, integrates, and proves value.
It means your business systems are connected, cleaned and standardized into one trusted base that can feed reporting, automation and AI models alike. We map your systems and key decisions, connect the approved sources, clean the data and agree KPI definitions with named owners. The result is dashboards, reports and reusable data tables rather than one-off spreadsheets. Most clients see their first reliable dashboard within four to six weeks.
Yes, one report, one team or one process is usually the fastest way to prove value before expanding further. We agree the scope, connect the systems that area depends on, and deliver a working dashboard and clean dataset for it first. This keeps the first project small enough to finish quickly while still showing measurable improvement in report preparation time. Once proven, the same approach extends to other teams and systems.
We need access to the business systems in scope, a list of the reports or decisions the data supports, and business owners who can confirm which numbers are correct. From there we run short workshops to agree KPI definitions and document them so everyone works from the same figures. Clear access and an available owner are the two things that most affect how fast the first project moves.
A BI tool only displays data, it does not fix the underlying problem of systems holding different versions of the same number. Our service does the connection, cleaning and KPI agreement work first, then delivers into the reporting tool you already use or a new dashboard if needed. This means the numbers are consistent before anyone builds a chart on top of them. Value is measured by KPI consistency, pipeline reliability and user adoption, not just dashboard count.
Pricing is based on the number of systems connected, the complexity of the KPI definitions and the ongoing monitoring required, and we quote it after mapping your systems and reports. Most engagements start with a fixed-price pilot for one business area, then move to a monthly data operations fee once the pipeline is running. This keeps upfront cost predictable and ties ongoing spend to a working service rather than a large upfront build.
Proof
Where this work paid off
Travel and hospitality
Track rate parity and competitor pricing across booking channels
Rates drifted between the brand site, OTAs and wholesalers, and revenue managers only found out after the booking window closed. DataplexLabs monitored rates, availability and promotions across channels and compressed the reporting loop from weekly to daily.
Read the case study →Grocery and FMCG
See basket-level price position and promo waste across banners
Weekly price checks covered a few hundred lines while competitors changed thousands. DataplexLabs tracked competitor shelf and online pricing across banners, matched products at pack and variant level, and showed where promotions were funding volume that would have sold anyway.
Read the case study →Next step
Discuss your use case
Bring one pain point, a data source, a workflow, a margin question. We'll come back with a focused assessment and a clear ROI hypothesis.