Push generative AI to its limits
Adding more prompts to automate further and further is no longer a solution!
Deploy your AI
Get sovereign, production-ready generative AI that can handle your most complete and complex tasks all the way through.
Move beyond copy-paste to the production of complex, ready-to-use deliverables, friction-free.
Advanced professional writing
Targeted content analysis
Content prioritization
Deliverable structuring
Automatic integration into document templates
Advanced prompt engineering
Want to take your prompts and generative AI task automation to the next level?
Advanced prompt engineering expertise
Generating results with generative AI is now accessible to everyone.
But as soon as you make that output more complex, you quickly run into model limitations: lost context, ignored instructions, unstable results as updates roll out…
Making these uses reliable requires a fine-grained understanding of the models and the ability to interact with them in a structured way.
Knowledge base creation
- Formatting aligned with the specific requirements of the model being used
- Smart pre-selection of the information that is actually useful and necessary for the task
Context optimization
- Streamlining instructions — limiting the stacking effect
- Removing contradictions, including implicit ones
- Ensuring consistency across ideas
Integration and maintenance
- API provided by Neovision
- Direct integration into your tools or via compatible connectors
- Monitoring model updates
- Prompt adjustments based on model evolution
FAQ
Common questions about GenAI
Can I do prompt engineering myself?
There’s nothing stopping you from doing it yourself, and it can work well for building a proof of concept (POC) on your own.
However, automating an entire workflow involving advanced, complex tasks while maintaining a high level of performance and reliability requires in-depth technical knowledge of how generative AI models behave.
Understanding the engineering behind how these models work, as well as their specific characteristics, is essential to building a fully automated system that delivers the expected results without compromising quality. In practice, the expertise of an AI engineer quickly becomes necessary.
Can generative and non-generative AI components be combined within the same solution?
Yes
Generative AI can enhance traditional pipelines (search, validation, extraction) while leaving classical models to do what they do best (speed, accuracy, controlled cost). The right combination gives you the best of both worlds.
Why use a proprietary RAG if a general-purpose LLM is sometimes enough?
To be in control of your data, reduce exposure to external clouds, and ground responses in your own sources of truth. You control the scope, freshness, and traceability.
Why use an LLM for extraction if it is possible to do without one?
Without an LLM, things work very well when document structures are stable (standardized formats). As soon as the structure varies from one file to another, an LLM provides the flexibility needed to maintain both accuracy and coverage.
Why work with an AI agency like Neovision to integrate generative AI?
→ The added value of AI experts and engineers:
- Continuous monitoring: Regular tracking of the most relevant models and tools.
- Pragmatic approach: Selecting and integrating the models best suited to your specific context.
→ The added value of a generative AI solution built by Neovision:
- Data sovereignty and security by design.
- Consistent results over time (unless a specific request is made to use a non-open-source model).
- An architecture designed for scalability (models and infrastructure).