Hello,  
hila

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Build and deploy non-hallucinating GenAI applications on structured and unstructured data

LLMs alone don't solve business problems

LLMs hallucinate.
hila has the components to make generative AI useful.


The Foundation of
GenAI in the Enterprise

The Proof

Anti-Hallucination

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

Custom and Local LLMs

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

Agentic Approach

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

LLMOps

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

The need for LLMOps

Monitoring cost, quality, variability and reliability of your LLMs provides measurable, trackable returns on your investment.

Robust capability, simple interface

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.

Cost

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.

Quality

We monitor the relevance of the answer to the question and compare it to similar previously returned, high-quality answers.

Variability

We monitor the latency of the response, specifically we see how long it takes for the LLM to respond and the overall latency.

Reliability

hila Monitoring has a richer function set that includes root-cause analysis, hotspot analysis, model comparison, policy management and outlier analysis.

Cost

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.

Quality

We monitor the relevance of the answer to the question and compare it to similar previously returned, high-quality answers.

Speed

We monitor the latency of the response, specifically we see how long it takes for the LLM to respond and the overall latency.

Robust capability, simple interface

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

Application monitoring

hila Monitoring has a richer function set that includes root-cause analysis, hotspot analysis, model comparison, policy management and outlier analysis.

Partners

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How we fit in your landscape

Security with your data

Your questions, answers and data remain private and behind a firewall. We are SOC2 and ISO27001 certified.

Structured, Unstructured

We provide a system that can flexibly work across structured and unstructured data types.

Deployment Agnostic

hila Enterprise works across all cloud types and technology vendors as a unified AI layer.

Make your job easier

Ask unlimited questions. No hallucinations, just answers.

Contact us