Expertise is difficult to access.
Answers live across manuals, application notes, internal procedures and a few experienced people. Users need assistance that reflects the instrument and method in front of them.
Ground / Custom AI agents
An AI assistant that understands your instruments and methods.
Help users work with specialized knowledge without making them translate every question into a software procedure. We build custom AI agents around your documentation, scientific tools and domain expertise, with clear boundaries and evaluations for the tasks that matter.
ground / Conceptual model
The customer problem
Where the next capability gets blocked.
A generic chatbot stops too early.
Retrieving a paragraph does not complete a calculation, choose a supported operation or prepare a useful workflow. Your assistant needs specialized tools and skills.
A convincing answer is not enough.
Your scientific team needs a way to judge answers, inspect tool use and identify where the assistant should ask for clarification or hand control back.
What we build
A useful scope.
A reviewable result.
We begin with one user group and a representative set of tasks. Your domain experts define useful behavior; we turn that into an assistant that can be evaluated and extended.
- 01
Task-specific knowledge and skills
Connect selected procedures, reference material and scientific tools. Define the skills needed for method assistance, calculations, instrument support or workflow preparation.
- 02
An interface in the right place
Deliver the assistant within a suitable web application or existing product workflow. Agree identity, access to information and the point where a user reviews a proposed action.
- 03
An evaluation set with your experts
Use representative questions and tasks, expected behavior and failure examples to assess grounded answers, tool selection and appropriate uncertainty.
- 04
A path from advice to action
Add supported instrument operations through a defined interface when needed. Action workflows can include modeled checks and approval; an advisory assistant does not need every execution layer.
Relevant engineering
LiquidBridge demonstrates skill-based planning and validation for a modeled liquid-handling workflow. It is an engineering demonstration, separate from our completed client software projects.
Before we start
A few practical questions.
How is this different from a chatbot over our documents?
Document retrieval can be one part. A custom agent can also use approved scientific tools and specialized skills to complete a defined task. We select the smallest useful scope and evaluate it with your domain experts.
Can the assistant work inside our existing product?
Yes, we can scope an integration with your current interface and backend. We assess the user experience, identity, data access and deployment requirements before choosing the architecture.
Does an assistant have to control an instrument?
No. Knowledge assistance, method support and workflow preparation can be useful on their own. Physical actions require an agreed integration, permissions and execution controls.
Can it use our own scientific methods?
We can turn accessible methods, calculations and procedures into selected skills and tools. Your domain experts remain essential for defining correct behavior and evaluating representative tasks.
Your next project
What’s next for your instrument?
Tell us what you want to connect, simplify or automate. Let’s define the first useful step together.