Skip to main content
Data services for business and AI teams

Better decisions. Automated work. Smarter AI

We collect data from websites and business systems. We prepare model-ready datasets for ML and LLM teams. We automate repetitive work, and we deliver clear pricing, supplier and import cost insights.

  • Web data collection
  • AI training data
  • Data integration & reporting
  • Workflow automation
  • Price monitoring
  • Supplier & import cost
  • AI safety & quality
SupplierFreightDutyRiskTrue costper unitEvery cost driver rolled into one true number

What we help you do

Six practical outcomes, in plain language

Every engagement starts with one agreed problem, a starting point and a target, so you can see the result rather than the plumbing.

Collect reliable data

Bring in useful data from websites, APIs, files, partners and business systems.

Prepare data for AI

Create clean, labeled and tested datasets for machine learning and LLM teams.

Connect systems and reports

Create one trusted view across sales, finance, operations and other systems.

Automate repetitive work

Reduce manual document entry, routing, approvals and information search.

Protect pricing and profit

Track the market and find pricing, rebate and billing issues earlier.

Improve purchasing and imports

See supplier risk, total cost and contract information more clearly.

A data partner for AI teams

Your ML and LLM teams should not spend most of their time fixing data. We collect, clean, label, review and refresh model-ready datasets for training, fine-tuning and evaluation.

  • Agreed dataset plan and collection rules
  • Cleaning, duplicate removal and sensitive-data handling
  • Labeling instructions with human or expert review
  • Training, validation and evaluation datasets
  • Quality reports, documentation and version history
  • One-time builds or ongoing managed data operations
Explore AI training data

Services

What we are able to do

Data extraction and monitoring comes first, because reliable data drives almost every other decision.

How we work

Understand, build, run and improve

Every project starts small. We expand only when the first step delivered against the measures we agreed.

01

Understand

Clarify the problem and owner, review your data, and agree success measures and a focused pilot.

02

Build

Create the data feed, dataset, dashboard or workflow, add quality checks, and test with real examples.

03

Run

Keep data fresh, deliver dashboards, files and alerts, and review exceptions with clear ownership.

04

Improve

Track outcome, quality, cost and speed, fix recurring issues, and report against agreed measures.

Proof, not promises

We publish what we can prove

No invented savings, no borrowed logos. Ask us for a sample output, a data quality report or a reference we are allowed to share.

  • A case study with the starting problem, the work and the measured result
  • A sample dashboard, alert, data file or workflow screen
  • A sample data quality or model evaluation report
  • A client reference we are allowed to publish
  • Our actual security and data handling practices

Common questions

Questions buyers ask us first

How we scope work, deliver it and keep your data safe. If your question is missing, ask us.

We are a data partner for business operations and AI teams. We collect and monitor data from websites, APIs, files and business systems, then clean and structure it so it is ready to use. On the business side this means pricing, supplier and purchasing insight and document automation. On the AI side it means model-ready training and evaluation data. Most engagements start with one workflow or one dataset and grow from there.

No, web scraping is one collection method we sometimes use, not the whole service. Our work also covers API connections, file processing, data cleaning, matching, quality checks, delivery into your systems and ongoing monitoring when a source changes. You get a maintained data service with defined quality rules, not a one-off script that breaks the first time a website updates its layout.

We work with purchasing, pricing, finance, operations, customer service and data teams on the business side, and machine learning, LLM, product and research teams on the AI side. Most clients are in manufacturing, wholesale and distribution, retail and e-commerce, import and export, consumer brands, logistics, healthcare distribution, and software and AI companies. Engagements are led by a functional owner such as head of purchasing or head of AI.

We start by agreeing the business problem, the data sources involved, the result you need and how success will be measured. From there we scope a focused first project, usually one workflow, one report, one dataset or one product group, rather than a broad rebuild. Most clients see a working result within two to six weeks, which then becomes the basis for expanding scope.

Work can be a fixed-price one-time dataset build, a recurring data feed, a managed monitoring service, or an ongoing data operations partnership billed monthly. The right model depends on whether your need is a single build, such as a training dataset, or continuous, such as competitor price tracking. We agree scope and pricing before starting so there are no surprises once the pilot is done.

Most pilots deliver a working result in two to six weeks, depending on the number of systems, sources and the complexity of the data. A single document workflow or a competitor price feed on one product category can move faster than a multi-plant supplier dashboard. We agree a concrete milestone upfront so you know exactly what the first delivery will include.

Yes, in most cases you do not need to replace anything you already run. We connect to the systems you have, such as your ERP, CRM, support platform or cloud storage, and deliver data to your database, dashboard, API or approved business tools. We only recommend a new tool when your current setup genuinely cannot support the result you need.

We agree data sources and permitted use before any collection starts, collect only the fields needed for the task, and identify data that must be restricted, masked or removed. Access is limited to approved people and services, and we agree in advance how long project data is kept. For regulated industries, we follow the access and retention rules your compliance team sets.

Only in cases you explicitly approve, and never by default. Uncertain, sensitive or high-value cases are routed to a person for review, along with the source information and the reason the case was flagged. Every workflow keeps an audit record of what data was used, what the system recommended and what a person decided, so the process can be checked later.

Either works, depending on what you need. Some clients need a one-time dataset, such as a training set for a specific model or a single profit-leakage review, and the engagement ends once it is delivered. Others need continuous work, such as price monitoring or document processing, which runs as an ongoing monthly service. We scope each engagement to match the actual need rather than defaulting to a long contract.

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.

Get a focused reply within one business day

One business-day response · NDA on request · No newsletter spam.

Book a meeting

Talk to a data and AI lead, not a sales rep

Pick a 30-minute slot. Bring one problem. You leave with a scoped approach and a rough ROI range.

  • 30 minutes
  • Video call
  • Reply within 1 business day