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Generative AI services

Generative AI is already a gamechanger — but what’s actually working?

Generative AI is transforming everything from automation to creative work. But how much of the hype holds up? Many companies experiment with AI without a clear direction and end up with impressive but ultimately useless outputs.

We take a different approach. At Trueimpact.ai, we help companies use generative AI to solve real problems and create tangible value. With a strong network of specialized partners — and deep insight into their actual use cases — we don’t just talk about potential; we show what works in practice.

What kinds of generative AI projects do we work on?

AI can do much more than generate random images or write average content. We help companies use the technology to:

  • - Automate content creation without sacrificing quality. AI can generate marketing copy, product descriptions, and legal documents — but it requires the right adaptation to avoid sounding generic.

  • - Boost personalization at scale. AI can deliver targeted product recommendations or generate unique communication based on customer data.

  • - Accelerate design and creativity. We’ve helped companies cut down product development time by using AI to create fast prototypes and mockups.

  • - Streamline software development. AI can write code, find bugs, and automate testing — significantly speeding up development workflows.

  • - Generate synthetic data. AI can produce realistic datasets to support better decision-making.

When we start a project, we always ask: Is the goal primarily to reduce costs, improve quality — or both? We have experience balancing both outcomes, so you get the most from your AI investment.

What technologies do we work with?

We don’t use AI for the sake of AI — we choose the tech that makes the most sense in your specific context. Some of the platforms and tools we commonly work with include:

  • - OpenAI, Anthropic Claude, and Google Gemini for language understanding and text generation
  • - Stable Diffusion and DALL·E for image generation and design
  • - Hugging Face models for specialized AI tasks
  • - Fine-tuning and RLHF (Reinforcement Learning from Human Feedback) to optimize models for specific business needs

- When do generative AI projects fail — and when do they succeed?

When do Generative AI projects fail and when do they succeed?

We’ve seen many AI projects fail — often for the same reasons:

  • - Unclear business objectives.Starting with a “we need to use AI for something” mindset often ends in an expensive gimmick.

  • - Too much complexity too soon. It’s tempting to build advanced AI systems, but simple solutions often deliver faster results.

  • - Poor input data. AI models are only as good as the data they’re trained on. Biased or low-quality data leads to useless outcomes.

  • - Too little human oversight. AI can produce huge volumes of content, but it needs proper quality control to be usable.

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Our approach is hands-on: We focus on delivering solutions that actually work in your daily operations — not just in a polished demo.

Do you have a relevant project?

If you're thinking about implementing any form of generative AI, let’s talk. Thanks to our large network of specialized partners, we likely know of similar cases related to your project — and can advise and inspire based on real-world examples.

Write to us, call us, or fill out the form below.