AI That Is Built Exactly for Your Business.

Off-the-shelf AI tools were designed for generic use cases. Your business, your customers and your language are not generic. Revolab engineers custom AI solutions — from fine-tuned language models and speech recognition to voicebots and enterprise AI platforms — built around what you actually need.

Three Custom AI Capabilities. One Team.

Every engagement starts with your requirements and ends with a production-ready system that is maintained, monitored and improved over time.

SERVICE 1

Custom Language Models & LLM Fine-Tuning

General-purpose LLMs are trained to be average across everything. We fine-tune or build from scratch language models calibrated for your specific domain.

Domain Fine-Tuning — Example Output Comparison

+61%

Task accuracy in financial domain

-44%

Hallucination rate vs. base model

6wk

Typical time to production

100%

Your data, your model ownership

SERVICE 2

Localised Speech Recognition & Transcription

Global speech models perform well on American English. Your contact centre handles Manglish over a mobile network, Kelantanese dialect at a noisy counter, or Levantine Arabic across a call centre in Amman. We build ASR models that work in your actual environment.

Live Transcription — Multilingual Call Centre

00:04

Agent

Hello, terima kasih kerana menghubungi kami. Ada apa yang boleh saya bantu? BM

00:09

Customer

Eh I nak tanya pasal my Unifi bill la, kenapa naik suddenly?  MANGLISH

00:04

Agent

Boleh confirm your account number? I check sekarang. MIXED

00:04

Agent

1234567. And also my router tak dok signal lah lately. DIALECT

Auto-generated call summary: Customer enquiring about unexpected bill increase and connectivity issues. Account 1234567. Both issues flagged for follow-up. Sentiment: frustrated > neutral.

SERVICE 3

Personalised Recommendation Systems & Behavioural AI

Your customers leave signals everywhere — what they browse, what they buy, when they leave and what they come back for. We build recommendation engines that turn those signals into personalised experiences at scale, driving higher average order value, longer sessions and stronger retention.

Personalised Output

Customer Signal

1

Behavioural data ingestion

Collects browse history, purchase patterns, session depth and search queries in real-time.

2

Customer segment modelling

Groups users by affinity, lifecycle stage and predicted intent — updated continuously.

3

Personalised recommendation generation

Produces ranked product lists, content blocks and offer variants per individual user.

4

Multi-channel delivery

Pushes recommendations to web, app, email and WhatsApp simultaneously.

5

Closed-loop learning

Tracks clicks, conversions and revenue impact — model improves with every interaction.

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