Put large language models to work on your documents, data and workflows.
Generative AI pays off when it is connected to your own documents, systems and processes. Noviant designs and builds generative AI solutions on AWS Bedrock and Hugging Face, from serverless intelligent document processing to multi-agent workflows that complete tasks across your applications.
We start with architecture and a roadmap, so each use case has a clear owner, data source and measure of success before anything is built.
Agentic and composite AI workflows where specialised agents plan, retrieve and act across your applications, built on AWS Bedrock.
Serverless intelligent document processing (IDP) that reads, classifies and extracts information from documents at scale.
Custom fine-tuning of open models from Hugging Face so outputs match your terminology, formats and tone.
Use-case selection, data readiness, model and platform choices, security and cost, sequenced into a practical roadmap.
Deploy on AWS, on GPU clusters in colocation, or on a LiquidEdge AI POD when you need dedicated capacity.
Identify the processes and documents where generative AI saves the most time.
Choose the architecture, models and data flows, and agree on how success is measured.
Develop and test the workflow on AWS Bedrock or Hugging Face models with your data.
Deploy, monitor quality and cost, and extend to the next use case on the roadmap.
Certified since October 26, 2019; certified to ISO/IEC 27001:2022 since October 26, 2025 (valid through October 25, 2028). Certificate No. 382119.00, issued by DEKRA Certification, Inc., an ANAB-accredited certification body. Scope: Managed services including Cybersecurity, Cloud Solutions, Data Analytics, and Data Infrastructure.
Helping state and city agencies meet their Article 15-A goals for minority and women-owned business participation.
AWS Bedrock for managed foundation models and agent workflows, and Hugging Face for open models and fine-tuning. We can also deploy on GPU infrastructure you control.
Several AI agents, each with a defined role, work together on a task: one might retrieve documents, another draft a response and another check it, all connected to your systems.
Yes. Document ingestion is often the first project: we read and extract information from your existing files so it can be searched, summarised or fed into other systems.
Not always. Many use cases work well with a foundation model and your data retrieved at run time. Fine-tuning helps when you need consistent formats, terminology or tone.
With an architecture and roadmap session. We map candidate use cases, check data readiness and recommend the first project with the best return.
