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Thinqmesh

AI Applications

AI Products That Remain Dependable Once People Rely on Them

We build assistants and agents on your own data, with evaluation, access control and cost tracking established before they reach your teams.

Our Point of View

A dependable AI product gives answers that hold on your data, respects each person's permissions and stays affordable in daily use. That is the standard we build to.

The Situation

A dependable AI product gives correct answers on your data, respects permissions and stays affordable once in regular use. These qualities come from testing and engineering as much as from the model, and they are strongest when they are designed in from the first day, before a product reaches its users.

Our Approach

We build evaluation in from the start, testing answers against real examples from your work so that quality is measured. The model is chosen on answer quality, running cost and where your data may go, and the design allows it to be changed without a rebuild. Anything high-stakes keeps a person approving the result.

What We Deliver

From a Useful Answer to a Dependable Product

  • Assistants on Your Data

    Answers to questions from your documents and systems, with the source shown each time so that your teams can check it.

  • Agents That Carry Out Tasks

    Software that completes multi-step tasks, with a person approving the steps that matter.

  • Document Processing

    Invoices, forms and contracts read and turned into checked, structured data.

  • Evaluation

    Answers tested against real examples, so that you can see quality as a measured score.

  • Access and Privacy

    Controls that ensure the AI sees only what each person is permitted to see, together with an activity record.

  • Cost and Quality Monitoring

    Quality and spending tracked in production, so that any change is seen early.

How We Engage

Your First Version in Four Weeks

Your first working feature arrives within four weeks, and the full engagement runs to six. Week one also produces an evaluation set and a measured score on your own examples, which shows whether AI or conventional software is the right tool before further investment.

Configuration on Your Data

We stand up the platform and load it with data representative of your business. By the close of week one, your stakeholders are reviewing a working system.

Expected Outcomes

What Leadership Should Expect to See

  • Answers That Can Be Verified

    Each answer shows its source, drawn from your own documents and systems, so that anyone can check it before relying on it.

  • Quality You Can Measure

    An evaluation set built from real examples shows how the product performs before launch, and monitoring continues that measurement in production.

  • Running Costs in View

    Quality and spending are tracked in production, so that leadership sees the running cost of the product as its use grows.

Industries

Where This Work Applies

  • Agents can read documents and prepare multi-step work, while a person approves what matters and an activity record shows what was done.

  • Assistants draw on your own documents and show their sources, access follows each person's permissions, and high-stakes results keep a person approving them.

  • AI features are added to products with evaluation and cost tracking from the outset, and with a design that allows the model to change without a rebuild.

Insights

Perspectives on AI Applications

Frequently Asked

Questions From Prospective Clients

Which AI Model Do You Use?
We select the model for each job according to answer quality, running cost and where your data is permitted to go. Those three considerations can pull in different directions, so we test against real examples from your work before settling on one. The design also allows the model to be changed later without a rebuild, which keeps your options open.
How Do You Prevent It From Inventing Answers?
The AI answers from your own documents and systems, and it shows the source each time so that anyone can check it. Before launch, answers are tested against real examples, which gives you a measured view of quality. Anything high-stakes keeps a person approving the result before it counts.
How Do You Control What the AI Can See?
The AI is limited to what each person is permitted to see, so every answer stays within that person's own access. Access controls and an activity record are part of what we deliver, which gives your organisation a record of what was done. Quality and spending are monitored in production alongside them.
How Do You Stop an AI Agent From Taking the Wrong Action?
A person approves the steps that matter, so anything high-stakes has human sign-off. Agents carry out multi-step tasks on your behalf, with an activity record of what was done and access limited to what each person may see. Answers are tested against real examples before launch, which gives you a measured view of quality.
How Will We Know What the AI Costs to Run?
Spending is tracked in production alongside quality, so that you can see what the product costs as its use grows. Running cost is also one of the three factors in choosing the model, together with answer quality and where your data may go. Because the design allows the model to change without a rebuild, you can revisit that choice if the balance shifts later.
What If Testing Shows Conventional Software Is the Better Fit?
We recommend conventional software, before further investment is made. Week one produces an evaluation set and a measured score on your own examples, so that decision rests on evidence. You can also bring the question your team answers repeatedly to the first call, where we assess whether AI can answer it reliably.
When Will Our First AI Feature Be in Use?
Your first working feature arrives within four weeks, and the full engagement runs to six. Week one produces an evaluation set and a measured score on your own examples, before anything is built on top of it. The scope is agreed in writing before work begins, so both parties can see what has been delivered.
Can It Read Invoices, Forms and Contracts Into Structured Data?
Yes. Document processing reads invoices, forms and contracts and turns them into checked, structured data. The results are tested against real examples from your work, so accuracy is measured, and anything high-stakes keeps a person approving the result before it counts. Access controls and an activity record apply to this work as they do to assistants.

Explore Further

Next Step

Book an Appointment

Arrange a complimentary 30-minute conversation, with no obligation. You will leave with a candid view on whether the initiative is worth building and, if it is, a scope and a date, with the cost worked out together on the call. Alternatively, send an enquiry and we will respond.

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