AI that earns its keep, or we turn it off
Plenty of AI projects exist so a company can say it has one. As an AI integration company working with clients in Sri Lanka and abroad, we start from the boring question first: what is actually eating your team's time, and can AI take it off their plate without adding a new mess to manage?
What you end up with
- A working feature inside the tool your team already uses
- A written record of what it can and cannot do reliably
- Cost per month, measured rather than estimated
- An honest recommendation, including when the answer is not to build it
How the work actually goes
We start from the task, not the technology
We ask what your team does repeatedly that they resent. Answering the same customer question forty times a week, retyping invoices, hunting through documents nobody indexed. If nothing on that list is expensive enough to justify the work, we tell you and stop here.
We prove it on your real data first
Before any integration, we run the idea against your actual documents and messages, and show you where it gets things right and where it gets things wrong. Demos on tidy sample data are how AI projects end up disappointing everyone.
It goes where the work already happens
The feature lands inside the system your team is already in, not in a separate tool they have to remember. We design for the case where it is unsure, because a model that admits it does not know is far more useful than one that guesses confidently.
We measure it, and we are willing to switch it off
You get the running cost and a simple measure of whether it is actually saving time. If it is not, we say so and remove it. An AI feature nobody uses is worse than no feature, because it still costs money every month.
What we build it with
We're not tied to one provider. The model gets chosen per job, on accuracy for your task, running cost, and where your data is contractually allowed to go. We'll tell you plainly which one we picked and why.
- Anthropic Claude API
- OpenAI API
- Self-hosted open models (Llama, Mistral)
- pgvector
- Pinecone
- TypeScript
Questions people ask us
- Will my company data be used to train someone's model?
- Not with the setups we use. We work with business API tiers where your inputs are not used for training, and we will show you the specific provider terms in writing before anything is connected.
- What happens when it gets something wrong?
- We design for that from the start rather than pretending it will not happen. Anything customer-facing either shows its source so a human can check it, or hands over to a person when its confidence is low.
- How much does it cost to run?
- It depends entirely on volume, and anyone quoting a flat figure before seeing yours is guessing. The pilot exists partly to measure this, so you get a real monthly number before committing.