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Applied artificial intelligenceThe lab

The AI Lab: experiment, measure, document

The PartITech Lab tests RAG architectures, models, data and evaluation methods before integrating them into web products.

Applied R&D AI prototypes Emerging technologies

Applied research and development

Test technologies before recommending them

The Lab is PartITech’s applied research space for artificial intelligence in web products. We test architectures, libraries and evaluation methods to distinguish a promising demonstration from a genuinely operable solution.

This work informs our monitoring, open-source tools and architectural choices. It does not replace the analysis specific to each client project.

Experiment
Isolate a hypothesis and test it against realistic cases
Measure
Compare quality, latency, cost and constraints
Share
Document results, including limitations

Areas of work

Topics we put to the test

01

RAG and search

Chunking, indexing, hybrid search, citations, access rights and answer evaluation.

02

Models and inference

Models accessed via API or deployed on controlled infrastructure, quantisation, latency and cost.

03

Documents and data

Extraction, structuring, metadata and preparation of reliable corpora for AI processing.

04

Product integration

Tooling, observability, security, user experience and integration with existing applications.

Experiment protocol

An experiment must be reviewable

We define the question, dataset, metrics and environment before comparing results. This discipline limits conclusions drawn from hand-picked examples.

Read the publications
  1. 01State a testable hypothesis
  2. 02Build reference cases
  3. 03Trace versions and parameters
  4. 04Measure gaps and failures
  5. 05Document usage limits

From Lab to product

Turn a finding into an architecture decision

An experiment becomes useful when it informs a trade-off: selecting a model, defining a RAG strategy, sizing infrastructure, establishing an evaluation protocol or abandoning a fragile path.

Your next product

Give your ambition a solid foundation.

Tell us about your context, constraints and expected outcome. We will reply with a concrete initial technical perspective.

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