GENERATIVE AI APPLIED TO PRODUCT

Integrate generative AI where it creates real value

We design concrete use cases for content generation, assistance and automation, aligned with your business needs rather than showcase effects.

Generative AI built for outcomes

What you get in the first weeks

  • High-ROI use case identification
  • Model selection adapted to your constraints
  • Rapid prototyping and validation
  • Product integration and production deployment

They trust us

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Our commitment

We deploy generative AI that solves real problems, not just impresses in demos

Generative AI is powerful, but only when applied to the right use cases with the right guardrails. We identify where LLMs, text generation and AI-powered content workflows create genuine business value.

At Inprogress, every generative AI implementation is evaluated against cost, quality, reliability and user adoption before reaching production.

Our responsibility

Production-grade generative AI with full cost and quality control

Generative AI in production requires careful engineering: prompt design, output validation, cost management and continuous quality monitoring. We take responsibility for building systems that remain reliable and cost-effective at scale.

At Inprogress, we ensure your generative AI features deliver consistent value without runaway costs or unpredictable outputs.

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Why Inprogress?

Use-case driven approach

We start from your business problems, not from the technology, to identify where generative AI creates the highest ROI.

Production guardrails

We implement output validation, content filtering and fallback mechanisms to ensure safe, reliable AI behavior.

Fast prototyping

Working prototypes are delivered within days so you can validate the value before committing to full integration.

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Frequently asked questions

We work on content generation, document summarization, intelligent search, conversational assistants, email drafting, report automation and custom LLM-powered workflows.

The right use case depends on your business context, data availability and expected ROI.

We work with OpenAI, Anthropic, Mistral, open-source models and fine-tuned solutions depending on your requirements for cost, performance, privacy and latency.

Model selection is always driven by your specific constraints, not by technology preferences.

We implement token optimization, caching strategies, model routing and usage monitoring to keep costs predictable and aligned with business value.

You get full visibility on AI spending with alerts and optimization recommendations.

Yes. We integrate AI features directly into your existing product through APIs, ensuring a seamless user experience without disrupting your current architecture.

The integration is designed to be modular so AI features can evolve independently.

We implement evaluation frameworks, human-in-the-loop validation where needed, automated quality checks and continuous monitoring of output accuracy.

Every deployment includes guardrails to prevent hallucinations, inappropriate content and off-topic responses.

Let’s talk about your project

A web or mobile application to launch, or a product to accelerate?
Book 30 minutes to align on the right next step, without wasting cycles.
See our work