NLPPeople
Language AI and NLP consulting

Language AI and NLP consulting

NLPPeople helps companies decide what to build with language technology, prove that it works, and put the right team behind it. Typical projects: search, information extraction, text classification, chatbots and conversational systems. We have connected language technology specialists with employers since 2013.

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or email info@nlppeople.com

What we help with

Three kinds of engagement, from the first conversation to the handover.

Product definition and validation

We turn a business problem into a product roadmap, success metrics and a minimum viable product that tests the riskiest assumption first.

Team building and project management

We assemble the project team from our network of thousands of language AI researchers and engineers, and manage the work from kickoff to delivery, with full transparency on time and budget.

Applications built on large language models

We help you choose between prompting, retrieval, fine-tuning and a smaller model, and set up the evaluation that tells you whether it works.

Prefer to hire the team yourself?

Post your roles on NLPPeople, where AI and language technology specialists already look for work.

Post a jobBrowse language AI jobs

We say no when NLP can’t deliver

Most providers say yes to every order. We start with a short evaluation, and if current technology cannot deliver what you need, we tell you and send you the research directions worth watching.

If we take the project, we commit to delivery against the scope and the success metrics we agree with you up front. You see our method, our time and budget estimates and the profile of the experts we will use.

How an engagement works

Four steps, and you can stop after the first one.

  1. Evaluate.

    A short feasibility analysis of your idea against what the technology can do today.

  2. Define.

    Roadmap, success metrics and the MVP that will validate the idea.

  3. Build.

    Experts selected from our network, managed to a plan you can see.

  4. Hand over.

    Working software with documentation and an explanation, so your own team can take it forward.

Case studies

Three projects we delivered.

Chatbot for a project management product

The problem
A software company wanted a chatbot inside its product but had no NLP expertise.
What we did
Built a proof of concept from scratch that understands simple project-management requests, handles small talk, connects to the client’s backend and works in Slack.
The result
Delivered on time, with documentation. The client’s team then built it into a product-ready chatbot and released it to end users.

Neural machine translation for e-commerce product descriptions

The problem
A fast-growing mass-market retailer needed multilingual product content at scale.
What we did
Took ownership of data collection, processing, training, testing and quality evaluation, and delivered a customizable MT API with pre-trained systems for the four languages that mattered most commercially.
The result
At the time, quality measured by customer usability and linguistic quality was significantly higher than public online engines, and content could be published with minimal human checking, cutting time to market and translation cost.

Automatic text generation for a product catalog

The problem
The same retailer needed product descriptions in several languages, generated from structured product data.
What we did
Designed and built a deep-learning text generation system that turns product records into near-human descriptions in three languages at once.
The result
The next step was personalising descriptions for different customer groups.

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Frequently asked questions

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Hire talent

Post a job on NLPPeople from €50.

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Not sure NLP is the answer? Ask us.

Send a short description of your idea. We will tell you whether the technology can deliver it and what we would do first.

Request a scoping call