Custom AI systems · Singapore

When manual work limits the business you can take on.

Turn research, reporting and scattered knowledge into work your team can use. We build custom AI systems around the workflow holding your business back.

Where we can help

More opportunity. Less work in the way.

Market intelligence

10,000+

company websites researched monthly

Current company records with source evidence for commercial decisions.

Read case study · 3 min ↗

Healthcare

10 minutes

From consultation end to report draft

Editable drafts in the practice’s format, with clinician review and sign-off.

Read case study · 3 min ↗

Financial services

Answers within reach

For firms with 50 to 100 people

Find company information and prepare documents with sources and access controls.

Read case study · 4 min ↗

Your first engagement

See it work on your own workflow.

Around one monthTypical proof of concept. Timing depends on scope, data readiness and integrations.

  1. 01 · Choose the task

    Start with what’s getting stuck.

    Choose one recurring task. Agree the result that would make a build worthwhile.

    You leave withA clear scope and success criteria.
  2. 02 · Try it with your team

    Review real outputs.

    Try a working version with your data. Check quality and how much review it needs.

    You getA proof of concept you can evaluate.
  3. 03 · Make the next decision

    Know what’s worth taking further.

    Review the evidence together. Decide whether to refine, stop or prepare for production.

    You decide withEvidence from your own workflow.

Start with a description of the task and the result you want.

Discuss your first workflow

Before you commit

Is this right for your team?

Start with the question that would hold you back.

How do I know if our problem is worth solving with AI?

Look for work that repeats, holds up a valuable next step and has a result your team can check. Research that delays a sales conversation, reports that delay client delivery or information people keep searching for are useful starting points.

Pick one task. How often does it happen, who does it, and what gets delayed? Those answers help us assess whether a process change, existing software or a custom system is worth exploring.

Tell us about that task →
How do we judge whether it will be worth the money?

Compare the full cost with a specific business improvement: more client work your team can take on, following up on opportunities sooner or fewer corrections reaching customers.

Before building, agree what result would justify continuing. Evaluate the proof of concept against that result, including the effort people still spend checking its output. Budget for the build, usage and hosting, and ongoing support; the scope and expected volume determine the estimate.

Our team is already busy. How much will this need from us?

You’ll need someone who knows the task, representative examples and time to review working outputs. Kairos handles the technical build and integrations; your team explains what a useful result looks like and checks that we’ve achieved it.

We agree contacts, responsibilities and review milestones before the build. For the first conversation, a description of the task and the result you want is enough.

What if the proof of concept isn’t good enough?

Agree what would justify continuing or stopping before the build begins. Then check real examples for quality, corrections and staff effort. A useful draft still needs to save work after review.

If the result falls short, use the evidence to decide whether to refine the workflow or stop. Moving into production is a separate decision, with integrations, controls and support agreed for that stage.

Who can see our information, and who checks the AI’s work?

Before company information is used, agree the data sources, hosting, providers and access needed for the workflow. Start with the minimum access required, using connections that only read data where possible.

Define where people must review or approve outputs and how to handle mistakes. For example, the dental reporting workflow produces an editable draft, with clinicians giving final approval.

Data, access and review controls →