Generative AI

Generative AI services that fit how your business works

We add AI assistants, content tools and smart features to your software, with the option to run models on private servers.

What’s included

  • AI assistants
  • Content generation
  • AI in your ERP or CRM
  • Self-hosted models

Why generative AI

Where generative AI services earn their place

Our generative AI services focus on practical work: drafting, summarising, searching and answering questions inside the tools your team already uses. The aim is less repetitive writing and faster access to information, not a demo nobody opens twice.

We start with the task, not the model. If a simple rule or report would do the job better, we’ll say so, and our business process automation work may be the better fit.

When AI is the right answer, we choose between hosted models and open-source models on private servers, based on cost, privacy and the quality the task needs.

Good first uses for AI

  • Drafting product descriptions and emails
  • Summarising long records and notes
  • Answering questions from your documents
  • Generating images for content
  • Suggesting next steps in workflows

Generative AI services we offer

AI built into real products and processes, with your data handled carefully.

AI assistants and chatbots

Assistants for your website, app or internal tools that answer from your own content in your brand’s tone.

Content generation

Drafts for product descriptions, blog outlines, captions and emails, reviewed by your team before anything is published.

Content production

AI inside your ERP or CRM

Summaries, suggested replies and smart search added to the business systems your team works in daily.

Self-hosted AI models

Open-source language and image models on private servers, so sensitive data doesn’t go to a third-party API.

Image generation

Generated visuals for content and product ideas, with prompts and styles tuned to your brand.

AI features in your product

AI-powered features designed, built and tested inside your web or mobile application, not bolted on.

Web app development

How we deliver generative AI projects

We test the value early, before you commit to a full build.

  1. 1Find the use case

    We identify tasks where AI saves real time and define what good output looks like.

  2. 2Prototype with your data

    A small working prototype tests quality, cost and speed against real examples.

  3. 3Build it in

    The feature is integrated into your system with permissions, logging and human review.

  4. 4Measure and refine

    We review outputs, tune prompts and models, and adjust as usage grows.

AI in software we’ve built

We run AI on our own infrastructure before recommending it to anyone else.

Sublime Care Cloud

150+permission-controlled screens, driven by metadata

Flagship product · Modular ERP with self-hosted AI

Sublime Care Cloud

The problem

Businesses needing one system for shop, inventory, finance, HR and more.

What we built

A metadata-driven modular ERP, with an open-source language model and image generation hosted on its own servers.

OutcomeAI capability available to the platform without sending business data to an outside AI provider.

  • .NET 8
  • Angular 18
  • Flutter
  • Self-hosted AI
Read the case study
Faatura Cloud

Our product · UAE

Faatura Cloud

The problem

UAE contractors still estimating and quoting jobs in spreadsheets.

What we built

Cost estimates, quotations and 5% VAT tax invoices in one platform, in English and Arabic.

OutcomeAn approved quotation becomes an invoice in one click.

  • Angular
  • Arabic RTL
  • Multi-company
  • UAE VAT
Read the case study
Sublime Groceria

Our product · Grocery list app

Sublime Groceria

  • 433users
  • 253grocery lists
  • 1,462list items
The problem

Grocery lists, recipes and nutrition information spread across different places.

What we built

A Flutter app, a website and web app, with the admin in Sublime Care Cloud.

OutcomeLive on Google Play and the web, managed from Sublime Care Cloud.

  • Flutter
  • .NET API
  • SQL Server
Read the case study
See all our work

Privacy and control

Generative AI with your data under control

Many AI tools send every prompt to an outside service. For some tasks that’s fine; for customer records, pricing or internal documents it may not be.

Because we already run an open-source language model and image generation on our own servers, we can offer self-hosted AI where privacy matters, and hosted models where they’re the better value.

Either way, AI output is treated as a draft. Permissions decide who can use it, and people approve what matters.

What you get

  • A tested use case, not guesswork
  • Hosted or self-hosted model options
  • Role-based access and usage logs
  • Human review where it matters
  • Ongoing tuning and support

Generative AI services FAQs

Straight answers to the questions we hear most.

How much do generative AI services cost?

Costs depend on the use case, the volume of requests and whether models are hosted by a provider or on private servers. We usually start with a small prototype, so you can see output quality and running costs before committing to a full build.

Is our data safe when we use generative AI?

It depends on how the AI is deployed. With a self-hosted open-source model, prompts and data stay on private servers rather than going to an outside AI provider. With hosted models, we choose providers and settings carefully and avoid sending information the task doesn’t need.

Can you add AI to our existing software?

Yes. We can add AI features to web applications, ERPs, CRMs and WordPress or WooCommerce sites through APIs or custom modules. We look at where your data lives and how people work, then place AI where it removes a step instead of adding one.

Should we use a hosted AI model or a self-hosted one?

Hosted models are quick to start with and strong on general tasks. Self-hosted open-source models give more control over data and running costs, but need servers and maintenance. We compare both against your task, privacy needs and budget before recommending one.

How long does it take to build an AI feature?

A focused prototype can often be ready in weeks. Turning it into a production feature, with permissions, logging, review steps and integration into your system, takes longer and depends on scope. We deliver in stages so you can test real value early.

Have a task AI could take off your team’s plate?

Tell us what slows you down. We’ll tell you honestly whether AI is the right fix.

Give us a call

Talk it through with the team.

+92 331 6482 364

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