Generative AI Consulting and AI Development Services

generative ai . nlp and machine learning . data strategy

Experiment, innovate, and deploy Generative AI solutions tailored to your company. Put Large Language Models (LLMs) to work to automate business processes and enable users to use plain language to query your data.

Explore how AI can help your company to save time and increase productivity

When should you hire an internal team to develop AI solutions?

You should consider hiring a team of AI specialists after you have made progress through 5 key phases. These phases include:

  • 1
    Identifying and prioritizing use cases (business problems you want to solve)
  • 2
    Developing proof of concept projects and AI prototypes
  • 3
    Assessing the success of the early projects
  • 4
    Piloting one or more potential solutions with internal partners
  • 5

    Designing and testing repeatable business processes and data pipelines

What does a Generative AI consultant do?

As generative AI consultants, we use our experience in machine learning to develop business solutions that use large language models like ChatGPT, Claude, and LLaMA. We ensure AI solutions are developed responsibly and address real business challenges.

Man working on a Generative AI project at the computer

Image source: Generated by Midjourney AI

Why consider us for Generative AI consulting services?

Our team can be an extension of your team, particularly in the early stages. We work on an as-needed basis; you control the cadence and have the flexibility to move at a pace that is right for you. Working together, you will gain the opportunity to experiment, iterate, and engage internal stakeholders in the assessment of prototypes.

We stay on top of the latest developments in models, machine learning, and deployment techniques. An outside-in perspective, gained from years of experience in creating machine learning, NLP, and AI contributes unbiased perspective.

  • Identify use cases – Develop and prioritize a set of use cases to explore the practical business value of AI.

  • Create Prototypes: – Test datasets, approaches, tools and technologies for your company.

  • Hone AI prompts – Engineer prompts to optimize how large language models (LLMs) interpret and execute plain language instructions.

Top reasons why organizations will adopt generative AI?

72% say it will be to improve employee productivity (humans working in collaboration with generative AI)1

Generative AI for Industry 4.0

Apply AI and Machine Learning to Work Orders, Computerized Maintenance Management Systems, and Internal Documentation

You may never have thought of your company’s internal documentation as a source of data for analysis. However, AI, NLP, and machine learning techniques can be used to help automate the processing of these documents for insights, anomaly detection, and operational efficiency.

Work orders often contain valuable, but unstructured text data. What can you learn from work orders?

Automated Categorization: AI can help automatically classify or categorize work orders based on the description of the problem or request. This can help route the work order to the right team or personnel, improving efficiency.

Trend Analysis: By analyzing the language used in work orders, AI can help identify trends, root causes, or recurring problems, assisting in problem-solving and decision-making.

Predictive Maintenance: By processing work order data alongside other sources of information, AI can help detect patterns that predict future maintenance needs, enabling preventive action.

Anomaly Detection: By understanding the normal language pattern of work orders, AI can flag unusual or suspicious requests for further investigation.

In the era of Industry 4.0, operating and equipment logs are increasingly being automated and digitized. Our generative AI development services can help you with real-time monitoring and analysis, predictive maintenance, and more efficient operations.

  • Proven track record of successful enterprise deployment of NLP and machine learning
  • Expertise in NLP techniques such as fact extraction, named entity recognition, topic modeling, sentiment analysis, and text summarization
  • Leverages algorithms for deep learning and machine learning, including neural networks and large language models (LLMs)
  • Well-established AI development process optimized for large enterprises
  • Smoothly transition from Proof of Concept (POC) to project deployment
  • We help you stand up an in-house AI organization and shepherd your team to independence
  • Increase efficiency of manually-intensive business processes
  • Gain actionable insights from large amounts of unstructured text data
  • Extract data from documents, email, customer feedback, and narrative reports