LLMs hallucinate.
hila has the components to make generative AI useful.
In addition to RAG techniques, our system uses a consortium of models to review an answer for errors and improve its correctness. Our text2sql pipeline also uses multiple LLMs to eliminate hallucinations on structured data.
Benchmark testing revealed
Achieved 99% reliability
We utilize fine-tuned and local LLMs for anti-hallucination, text to SQL, language translation and vectorized embedding. This helps us improve accuracy, speed and efficiency, maintain privacy and work within your landscape.
Up to
96.42% improved accuracy
Our agentic solution enables the advanced extraction of tables, charts and metadata from hundreds of thousands of documents, with superior accuracy and lower cost.
Lowered cost by
4x
We analyze more than 200 billion inferences with sub-second responses on LLMs and other models. There are no large clusters required, and we sped up the policies to run on 1 billion records per day.
Up to
10,000x improvement
Monitoring cost, quality, variability and reliability of your LLMs provides measurable, trackable returns on your investment.
hila Monitoring alerts a user if any of the above features begins to deviate from the norm, and has more advanced capabilities, such as root-cause analysis, data heatmaps, outlier analysis and explainability.
We monitor LLMs based on a variety of factors, including overall cost, the cost of the questions and how efficiently the system provides an answer.
We monitor the relevance of the answer to the question and compare it to similar previously returned, high-quality answers.
We monitor the latency of the response, specifically we see how long it takes for the LLM to respond and the overall latency.
hila Monitoring has a richer function set that includes root-cause analysis, hotspot analysis, model comparison, policy management and outlier analysis.
We monitor LLMs based on a variety of factors, including overall cost, the cost of the questions and how efficiently the system provides an answer.
We monitor the relevance of the answer to the question and compare it to similar previously returned, high-quality answers.
We monitor the latency of the response, specifically we see how long it takes for the LLM to respond and the overall latency.
hila Monitoring alerts a user if any of the above features begins to deviate from the norm, and has more advanced capabilities, such as root-cause analysis, data heatmaps, outlier analysis and explainability
hila Monitoring has a richer function set that includes root-cause analysis, hotspot analysis, model comparison, policy management and outlier analysis.
Your questions, answers and data remain private and behind a firewall. We are SOC2 and ISO27001 certified.
We provide a system that can flexibly work across structured and unstructured data types.
hila Enterprise works across all cloud types and technology vendors as a unified AI layer.
