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Artificial intelligence and automation for business

We do not sell AI as a category. We apply it to specific tasks that currently consume hours of manual work: reading documents, classifying information, or finding one detail inside thousands of files.

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We help companies bring artificial intelligence into real business processes. We build solutions that analyse documents, extract information, automate repetitive tasks, let teams query internal knowledge, and turn large volumes of information into data people can actually decide on.

The starting point is never the technology. It is an identifiable task: someone spends hours transcribing invoices, the legal team cannot find which contract holds a clause, or service staff answer the same questions over and over. From there we assess whether AI adds something measurable, or whether conventional automation solves it better.

What it includes

Use-case assessment

We review candidate processes and separate the ones AI handles well from the ones it does not. A process with clear, stable rules is almost always better automated without language models.

Proof of concept on your data

Before committing to full development, we validate with real documents and real cases from your operation. If accuracy falls short of the intended use, you find out at that stage rather than later.

Development and integration

We build the solution and connect it to the systems where the information already lives: ERP, document repository, databases or the team's internal tools.

Controls and human oversight

We define which decisions the system makes and which require a person to review, with traceability of everything processed automatically.

Deployment and training

We put the solution into production and train the team that will use it daily, including what to expect from the system and what not to.

Tuning and follow-up

We measure results against real usage and adjust. AI-based solutions improve through that tuning; they are not finished on deployment day.

Business benefits

  • Time recovered from reading and data entry

    Processing invoices, forms or case files stops depending on someone transcribing them field by field.

  • Information you can actually find

    Search by meaning locates the right document even when nobody remembers the file name or the exact wording it contained.

  • Fewer repeated questions to the team

    An internal assistant over company documentation answers the frequent questions and leaves the team the work that needs judgement.

  • Decisions on data that used to be scattered

    Information trapped in PDFs, emails and loose documents becomes searchable and comparable.

  • Narrow, verifiable scope

    Each use case is validated on real data before it is built, so you know what to expect before investing.

How we work

  1. Identify the task

    We start from a specific, measurable process: how many hours it consumes today, who runs it, and what happens when it goes wrong.

  2. Assess feasibility

    We check whether enough data exists at the required quality, and whether the achievable accuracy is good enough for the intended use.

  3. Test on real data

    A narrow trial with documents and cases from your operation, with success criteria agreed before starting.

  4. Build and integrate

    Development inside the existing workflow, so the team does not have to move to yet another tool.

  5. Measure and tune

    Follow-up on real usage, correction of failing cases, and scope expansion only once the first one works.

Use cases we solve

  • Document analysis: reading contracts, invoices or case files and returning structured information
  • OCR: turning scanned documents and images into processable text
  • Data extraction: pulling specific fields from documents with varying layouts
  • Automatic classification: sorting documents and requests by type without manual triage
  • Semantic search: finding by meaning and context, not only exact matches
  • RAG: answers grounded in the company's own documentation, with the source cited
  • Internal assistants and AI agents for policies, manuals and procedures
  • Business chatbots connected to the organisation's real data
  • Automation of repetitive processes that depend on manual reading
  • Report and summary generation from scattered information
  • AI integration with the ERP, CRM and internal systems already in use
  • Document management with AI across archives and active documentation

Who this is for

Companies where document volume or scattered information has become a bottleneck: legal, administrative, HR, quality or customer service teams spending hours reading, classifying, transcribing or searching. Also organisations that want to evaluate what AI can do in their operation before committing budget, starting from one narrow case.

Why CoreTech

We integrate AI inside systems already in production, with the real constraints of a company: sensitive data, per-user permissions and processes that cannot stop. We are explicit about which use cases are worth it and which are not: a rule-based process is better automated with conventional development, and saying so avoids paying for complexity that adds nothing.

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Frequently asked questions

With one specific, repetitive, high-volume task: invoice reading, email classification, search across a document archive. A narrow case validates in weeks, produces a measurable result and tells you whether to expand. Starting with a broad, cross-company initiative is the most common way to finish none of it.

It is part of the design from the start: what information leaves your infrastructure, where it goes, under which permissions and under what agreement with the model provider. Some cases can be solved without documents leaving your environment. We define this with you before building, not after.

It depends on document quality and on how variable the layouts are. That is why the assessment runs on your real documents with agreed success criteria: if accuracy falls short of the intended use, it is better to know before development. For critical processes, automatic extraction is combined with human review of uncertain cases.

Not to operate it. The team works from the usual interface or from the system they already use. What you do need is someone from the area who knows the process and can validate results during rollout.

Yes, that is the normal scenario. We connect to Odoo, to other ERP and CRM systems, to databases and to internal tools through their APIs, so processed information lands in the system the team already works in.

When the process has clear, stable rules: conventional automation is cheaper, faster and more predictable there. It is also the wrong call when there is not enough data, when volume does not justify the effort, or when the process demands absolute accuracy with no human review possible.

Let's talk about your project

Tell us which task consumes the most of your team's time and we will assess together whether artificial intelligence is the right answer for it.

Message us on WhatsApp

+1 (809) 660-4499

Or if you prefer, write to us directly at ventas@coretech.do