Artificial Intelligence
With the advent of generative AI, we at Copods work with our clients across a range of domains to enable their products with AI which is capable, helpful, easy to understand and trustworthy. Some touch points include:
- Transparency and Trust: Providing clear explanations of AI functionality and decision-making processes to build user trust.
- User Control: We empower users to correct and control the AI’s understanding of a prompt to ensure they receive accurate results.
- Multi modal Inputs and Outputs: Based on various use cases, we’ve created experiences that deliver outputs in multiple formats, including those relevant to analytical software.
- Productivity with AI: AI is not the product but a feature integrated into workflows to accelerate them. Our thoughtfully crafted experiences leverage AI to help users complete tasks in context.
- Performance Optimization: With our deep understanding of RAG, Vector Embeddings, and other technologies, we’ve developed AI models that better understand and predict user needs.
- Ethical AI: We incorporate ethical considerations into AI design and development to mitigate potential biases and ensure responsible use.
Source: https://www.copods.co/practices/artificial-intelligence/
Nice work shipping it. What has been the biggest challenge since launch?
Nice work shipping it. What has been the biggest challenge since launch?
Great breakdown. What feedback have you had from early users?
Thanks! The strongest feedback has been around transparency. Users specifically call out when they understand why the AI suggested something, not just what it suggested. That's pushed us to keep refining how we surface reasoning in the UI.
Nice work shipping it. What has been the biggest challenge since launch?
Appreciate that. Honestly, balancing model performance with response speed has been the toughest part. Getting RAG and vector search fast enough that it doesn't break the user's flow.
Clear and practical, thanks. Did anything surprise you along the way?
Glad it was useful. The biggest surprise was how much users wanted control over the AI's interpretation of their input, not just accurate output, but the ability to correct the AI's understanding before it acts.
Thanks for writing this up. Bookmarking it for later.
Really glad it's useful, thanks for reading.
Appreciate the honesty here, most people only share the wins.
That means a lot. Thank you.
Interesting take. Would you still recommend this approach to someone starting today?
Yes, but with one caveat: we'd tell them to invest early in explainability and user control, not bolt it on later. It's much harder to retrofit trust into an AI experience than to design for it from day one.
Nice progress. What is the next thing you are focusing on?
Thank you! Right now we're focused on tightening the multimodal experience, making sure outputs map cleanly to different formats depending on the use case, especially for more analytical workflows.
Interesting approach. What was the hardest part to get right?
Thanks! The hardest part has been juggling quality and speed, getting RAG and vector search to run fast enough that they don't interrupt the user experience.
Interesting approach. What was the hardest part to get right?
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