NeoTek Solutions designs, builds and integrates generative AI solutions: applications built on large language models (LLMs) that draft, summarize and answer questions from your own data. We work with organizations that have large document collections, busy service desks or software products that need AI features. From our Nashville headquarters we take each project from first experiment to secure production, for clients across Middle Tennessee and the US.

An LLM can read, write and summarize language, but on its own it knows nothing about your business. We connect these models to your content, systems and rules so they give useful, trustworthy answers. That connecting work is what we deliver.

Who Needs Generative AI Solutions?

Our generative AI services fit operations, IT and business leaders who want more than a chatbot demo. Typical clients include:

  • Organizations with large volumes of documents, policies or records that staff struggle to search
  • Customer service, HR and IT help desk teams that answer the same questions every day
  • Software product teams that want to add AI features to existing web and mobile apps
  • Regulated organizations, such as healthcare providers and financial services firms, that need strong data controls

What We Build

Custom LLM Applications and RAG Knowledge Search

We build retrieval-augmented generation (RAG), so the model looks up relevant passages in your own content before it answers. Your AI answers from your documents, knowledge bases and databases, with references to its sources. That reduces inaccurate answers and keeps sensitive data under your control.

Typical solutions include enterprise knowledge search, policy and procedure lookup, and question answering across contracts or technical manuals. Not sure whether RAG or model fine-tuning fits your need? Read our guide on RAG vs. fine-tuning. To see how different RAG designs fit different problems, read RAG architectures explained.

AI Copilots, Chatbots and Assistants

We design conversational assistants for customer support, HR and IT help desks, sales enablement and internal operations. Each one connects to your business systems, follows your brand voice and hands off to a person when needed. Assistants can answer questions, look up records and guide users through common tasks.

Document Drafting and Summarization

Generative AI can produce first drafts of reports, letters, proposals and case notes from your templates and data. It can also summarize long records, meeting notes and email threads into short, consistent briefs. Your staff review and approve the output, so people stay responsible for the final result.

AI Features Inside Your Existing Applications

You do not always need a new system. We add AI features to the web and mobile applications your teams and customers already use. Examples include smart search, suggested replies, automatic tagging and in-app help. When a feature needs to act across several systems, we pair it with AI agents and automation.

How We Make Generative AI Work in Production

Model Selection

We choose the right model for each job, commercial or open source. The decision weighs cost, privacy, speed, accuracy and where the model can be hosted. Some use cases run best on a large hosted model, while others suit a smaller private deployment.

Evaluation and Monitoring

Before launch, we test each solution against a set of real questions and expected answers agreed with your team. After launch, we monitor answer quality, usage, cost and user feedback. This lets us catch problems early and improve the system over time.

Security and Data Protection

We build with access controls, encryption, private or enterprise model deployments where required and clear rules on what data the AI can see. Your data is not used to train public models. Our AI governance and security practice adds usage policies, guardrails and audit logging.

What You Get

  • A defined use case with agreed success criteria
  • A working solution connected to your content and systems
  • An evaluation set and quality report
  • Security controls, logging and human review steps
  • Monitoring dashboards for quality, usage and cost
  • Documentation and handover training for your team
  • Options for ongoing support and improvement

What Does a Generative AI Project Involve?

  1. Discovery

    We confirm the business problem, users, data sources and success criteria. If you are still choosing where to start, our AI strategy consulting can help.

  2. Data and architecture

    We review your content, access rules and systems, then design the solution and select models.

  3. Proof of concept

    We build a focused version with real data and test it with a small group of users.

  4. Production build

    We harden security, add integrations, complete evaluation and prepare monitoring.

  5. Launch and adoption

    We roll out in stages, train users and gather feedback.

  6. Improve

    We track quality and cost, then refine prompts, content and features as needs change.

Why NeoTek Solutions

Enterprise-grade generative AI needs clean data, the right architecture, responsible guardrails and people who understand your business. Our team combines application development, data engineering and IT consulting experience. We start with a clear use case, not a tool.

  • Business outcomes firstEvery project begins with success criteria your leaders agree on.
  • Model-neutral choicesWe recommend commercial or open-source models based on your needs.
  • Built to fit your systemsWe integrate with the platforms you already use, on Azure, AWS or Google Cloud.
  • Human oversight built inPeople review sensitive output, and every solution includes logging.
  • Local teamWe are headquartered in Nashville and work with clients across Middle Tennessee and the US.

Related Industries

Generative AI needs differ by sector. See how we approach it for healthcare and health tech, financial services and insurance, and music, media and entertainment.

How Can NeoTek Solutions Help You Ship Generative AI?

Demos are easy. Getting a generative AI solution into daily use, on your own data and under your own controls, is the part we do.

  • Work we deliverRAG knowledge search, copilots and chatbots, document drafting and summarization, plus AI features inside the applications you already run.
  • Built on your content and systemsWe connect models to your documents, knowledge bases and databases, and integrate with the platforms you already use.
  • What makes us differentWe use AI in how we build as well as in what we build, and we stay vendor-neutral instead of reselling one model or platform.
  • How we workShort cycles with AI-assisted delivery and human review, an evaluation set agreed with your subject-matter experts early and a working version you can try.
  • Skills on the teamAI and machine learning engineers, data engineers, cloud and security specialists and QA, so retrieval, integration, security and testing are covered by one team.
  • Your data stays yoursPrivate or enterprise model deployments where required, access controls and logging, and your data is never used to train public models.

Tell us about the questions your teams answer or the app you want to improve. Book a free AI consultation and we will walk through a practical first project.

Frequently Asked Questions

What do you build with generative AI?

We build knowledge search over your own documents, copilots and chatbots for service desks, and drafting and summarization tools for your staff. We also add AI features to the web and mobile applications you already run. Every build starts with a use case and agreed success criteria.

How do you keep answers grounded in our own content?

We use retrieval-augmented generation. Before answering, our systems retrieve the most relevant passages from your documents or databases, then write a response with references back to the source. Your staff can check where an answer came from.

Is our company data safe when we work with you?

Yes, because we design for it. We build with access controls, encryption, private or enterprise model deployments where required and clear rules on what data the AI can see. We never use your data to train public models, and every solution we ship includes logging and human oversight.

How long does a generative AI project with you take?

We can often deliver a focused proof of concept in a few weeks. Moving to production depends on how many systems are involved, how ready your data is and what security and compliance require. We agree scope, milestones and success criteria before development begins.

Do you offer generative AI consulting in Nashville?

Yes. We are headquartered in Nashville, Tennessee. We provide generative AI consulting and development to organizations in Nashville, Franklin, Brentwood, Murfreesboro and across Middle Tennessee, as well as clients throughout the United States.

Put Generative AI to Work on Your Own Data

Tell us about the questions your teams answer, the documents they write or the app you want to improve. We will help you find a practical first project. Book a free AI consultation

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