The short answer
Generative AI creates new content, such as text, images, code and summaries, in response to prompts. Agentic AI goes a step further by planning and taking actions with tools to complete tasks. iCreativez Technologies builds both: copilots, content and knowledge assistants powered by generative AI, and AI agents that act inside your systems, and helps you decide which approach each use case needs.
What our Generative & agentic AI services include
Assistants inside your apps or workplace tools that draft, summarise, explain and answer.
Marketing, product, support and internal content generated in your brand voice, with review workflows.
Answers from your documents and data, with citations and access controls.
Internal coding assistants, test generation and documentation tools for engineering teams.
Image generation and analysis, document understanding and voice interfaces.
Agents that research, plan and take actions across your tools, with approvals and limits.
Prompt design, model selection and fine-tuning for quality, speed and cost.
Quality testing, hallucination checks, content filters and brand-safety rules.
Generative AI or agentic AI?
| Generative AI | Agentic AI | |
|---|---|---|
| What it does | Creates or transforms content | Plans and takes actions to reach a goal |
| Typical output | Text, images, code, summaries | Completed tasks: records updated, tickets resolved |
| Human role | Reviews and uses the output | Sets goals, approves key steps, audits results |
| Main risks | Inaccurate or off-brand content | Unintended actions, excessive access |
| Good starting point | Drafting, summarising, Q&A | Repetitive multi-step tasks with clear rules |
Popular generative and agentic AI use cases
- Sales. Account research, personalised outreach drafts and meeting summaries, with an agent that updates the CRM.
- Customer support. Answer drafting from the knowledge base, and agents that resolve routine requests end to end.
- Marketing. Content briefs, drafts and variations, with an agent that schedules and reports.
- Operations. Document summarising and comparison, and agents that process requests across systems.
- Engineering. Coding assistance, test generation and an agent that triages bug reports.
How we work
- Identify. Choose use cases and decide whether each needs generative or agentic AI.
- Prototype. Build a quick prototype on real data to test quality and value.
- Harden. Add security, evaluation, guardrails and integrations.
- Launch. Roll out to users with training and feedback channels.
- Evolve. Improve prompts, models and autonomy based on results.
Ways to work with us
- Project delivery: an agreed scope, timeline and acceptance criteria, delivered by our team.
- Ongoing team: a small team that keeps building, improving and supporting your AI over time.
- Dedicated engineers who join your team through our IT Staff Augmentation Services, working in your tools and time zone. Typical rates are in our cost and rates guide.
Every engagement starts with an NDA. You own the code, models, prompts and documentation we create, and your data is used only for your project.
Our AI services
- AI development services in Pakistan
- AI automation services
- AI integration services
- Agentic AI implementation
- Custom AI development
- AI product development
- AI MVP development
- Enterprise AI solutions
- Enterprise AI & governance
- AI security
- AI strategy consulting
- AI talent & staff augmentation
See all our AI services in one place.
Ready to talk about Generative & agentic AI?
Tell us your goals and constraints. We’ll reply with a practical approach, timeline and estimate.
Frequently asked questions
What is the difference between generative AI and agentic AI?
Generative AI creates content in response to prompts. Agentic AI uses generative models to plan and take actions with tools, completing multi-step tasks toward a goal.
Which generative AI models do you use?
We work with OpenAI GPT, Anthropic Claude, Google Gemini and open-source models such as Llama and Mistral, choosing per use case.
How do you reduce hallucinations?
By grounding answers in your data with retrieval, showing sources, testing against real questions, and routing uncertain answers to people.
Can generative AI write in our brand voice?
Yes. We use style guides, examples and, where useful, fine-tuning, plus review workflows before publishing.
Should we start with generative or agentic AI?
Most organisations start with generative AI assistants, which are lower risk, then add agents for repetitive multi-step tasks once quality and controls are proven.
Is our data used to train public models?
Not with the enterprise AI services we use, which do not train on customer data by default. Private model hosting is also available.