Do you have a lot of text data and want to make it reliably accessible? Have you implemented an initial NLP system but need help to improve it? We have a solution for you. We develop expert systems that can, among other things, answer legal questions, summarize documents, and analyze political arguments for you. Talk to us if you want to tap into our knowledge of best industry practices and the latest NLP research to solve your problem.
Companies using NLP to automate internal processes (e.g., to search large document stores, chat with customers, summarize meetings) want reliable results. Asking the same question twice should produce the same answer too, algorithms should be predictable in how they interprets new data, and there must be a reliable way to verify source information and minimize hallucinations. Standard off-the-rack methods will only get you so far when tackling these challenges; developing advanced solutions takes expert skills and knowledge. That is where we come in.
To achieve reliable results in real-world use cases, the problem must be addressed holistically. To better understand how a model produces its prediction, we apply a combination of interpretability research methods, ground outputs in the source to ensure they can be verified, continuously monitor the model's predictions, and thoroughly evaluate them. Gaining a full picture of your model's performance, you will be able to identify and address potential mistakes before they impact your business.
Selection of current use cases:
- Making company knowledge “queryable” with retrieval-augmented generation (RAG)
- Bespoke summarization of meeting notes and customer service tickets that outperforms generic off-the-rack solutions
- Identifying the model with the best cost-benefit ratio for your problem
- Finetuning the model with your data to customize it to your context
- Ensuring the data privacy of your documents while using the latest large language model (LLM)
- Minimizing instances of hallucinations (made-up facts) in your system’s responses and attribution of outputs to specific parts of your knowledge base
Read our interview on how chatbots are becoming more personalized and reliable.
