Your work needs more than a general answer.
A useful answer often depends on knowledge that your team takes for granted. The model needs enough of that context to make a sound judgment.
Lala Labs
AI should understand the work. Too often, it just sounds like it does. We study the difference and help you close the gap.
Measure
Test where models struggle.
Tune
Teach them the work.
Preserve
Check what training changes.
Who We Are
A fluent answer can still miss the point.
A model can know the terminology and still miss the point of a question. Your team ends up redoing work the AI was supposed to handle.
Lala Labs studies how models arrive at a reading of a text, especially when the meaning isn’t spelled out.
We use that research to help businesses adapt models to their work. Evaluation is part of the process, so you can see whether a change helped.
Where Models Fall Short
You need to know why it went wrong.
Giving a model more information won’t help if it’s misreading what it already has. We investigate the error before recommending a fix.
The wording matters.
An omitted qualification or a poorly chosen word can change an answer’s meaning. We examine those details when we evaluate and improve model output.
Products And Services
What we build and advise on.
We help with model development from an initial review through deployment. We also build tools for working with AI-generated text.
Advisory And Implementation
Put your knowledge to work in a model.
Advisory
Help with pre-training, post-training, retrieval, and deployment, including decisions about what to build and how to test it.
Custom Learning Environments
Training tasks and feedback based on the work you need the model to do.
Domain Expertise
Train models on material from your field so they can apply it to the decisions your team faces.
LALA Benchmark
Test the abilities your work depends on.
Custom Benchmark
Evaluations built around your tasks, with enough detail to show where a model falls short and whether a revision addresses the problem.
Token-To-Information Optimizer
Reduce unnecessary text in model responses and agent instructions while checking that essential information survives.
Language Systems
Make model output easier to use.
SAM
Semantic Analysis Matching examines how a model interprets the terms and distinctions in your field, helping guide training on your own material.
AI2H
AI-to-human text generation edits model drafts for more natural writing. It cuts repetitive phrasing and adjusts the prose for its intended reader.
TAD
The Text Analysis Dashboard lets you review AI writing for clarity, tone, style, and how well it suits its audience.
Consulting and Advisory
Work out whether AI is useful here.
Have a system that isn’t working as expected, or a job you’re considering using AI for? Talk it through with us.
Enterprise Solutions
Show us where the model gets stuck.
Show us a model response that didn’t work and explain what you needed instead. We can investigate the cause and work out how to test a fix.
Discuss a model audit
Output Analysis
Example Review
Use of context
On topic
Answers the question
Partly
Unnecessary wording
Some
Tone
Consistent
Before: “It is important to note that further review may be beneficial.”
After: “This needs another look.”
Research
How well do language models understand language?
The LALA Benchmark examines how models interpret and use language. We look at individual abilities and patterns of error, and ask how they differ across models and stages of training.
Look closely at the answer.
Can the model explain a passage’s meaning, including what the writer leaves unsaid? We examine its interpretation rather than taking a fluent answer at face value.
Examine what changes after training.
We compare base and post-trained models to examine how training affects particular language abilities. An improvement on one task may come at a cost elsewhere.
Test what happens when context matters.
The same words can mean different things in different settings. We test whether models use the surrounding context to work out what a writer means.
Model Comparison
Training history matters.
We consider training stage and access to model weights separately. Open weights alone don’t tell you how much post-training a model has had.
Base models
Before instruction tuning
Open-weight models
Weights available to study
Hosted models
Tested through their APIs
Work With Lala Labs
What would you like your AI to do better?
Tell us what you’re trying to do and where the current results fall short. We’ll discuss whether we can help.
Contact Lala Labs