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> Design. Build. Run.

Generative AI Solutions

Most generative-AI pilots never reach production — they stall on data access, hallucination, security review, or runaway cost. RHC Solutions designs, builds, and runs generative AI that actually ships: assistants and copilots grounded in your own data, content and document automation, and retrieval systems — engineered with the security, governance, and evaluation that get them past your risk team and into daily use.

Generative AI uses large language models to create text, code, images, and structured output from natural-language instructions — and applied to a business, it automates knowledge work like drafting, summarizing, search, and support. RHC Solutions delivers generative AI end to end: we identify the highest-value use cases, build the solution on your data with retrieval-augmented generation (RAG) and guardrails, and run it in production with monitoring, evaluation, and cost controls — securely, on the cloud you already use.

> By the numbers
RAG
Grounded in your data to cut hallucination
24/7
Monitored, evaluated & cost-controlled in production
OWASP
LLM Top-10 controls built in from day one
30+ yrs
Security-grade engineering since 1994

What we deliver

GenAI Strategy & Use-Case Design

We assess where generative AI creates real value, prioritize use cases by ROI and feasibility, and define success metrics — so you build what moves the business, not a demo.

Assistants & Copilots

Domain-specific chat assistants and copilots that answer from your documents, systems, and policies — embedded in the tools your teams already use.

RAG & Knowledge Systems

Retrieval-augmented generation pipelines that ground model output in your own content, with source citations, so answers are accurate and traceable.

Content & Document Automation

Automated drafting, summarization, extraction, and classification across documents, email, and tickets — turning manual knowledge work into minutes.

LLM Engineering & Integration

Model selection, prompt and evaluation pipelines, fine-tuning where it pays off, and secure integration with your data and APIs across AWS, Azure, or GCP.

Secure & Governed Deployment

Guardrails, access controls, PII handling, audit logging, and human-in-the-loop review — the controls that get GenAI past security and compliance and into production.

How we engage

We work design–build–run. In Design, we run discovery with your teams to find and prioritize use cases, assess data readiness, and agree success metrics and guardrails. In Build, we develop the solution on your cloud — RAG pipelines, integrations, prompts, and evaluation harnesses — with security reviewed at every step. In Run, we deploy to production and operate it: monitoring quality and cost, tuning against real usage, and adding capability over time. Because we're security-first and vendor-neutral, we use the models and cloud you already trust rather than locking you into one stack.

> FAQ

Frequently Asked Questions

What is generative AI and what can it do for my business?
Generative AI uses large language models to produce text, code, and other content from plain-language prompts. In a business it automates knowledge work — drafting, summarizing, answering questions from your documents, classifying and extracting data — freeing people for higher-value work.
How do you stop the AI from hallucinating or leaking data?
We ground answers in your own content using retrieval-augmented generation (RAG) with source citations, enforce access controls so the model only sees what a user is allowed to, handle PII deliberately, and add evaluation and human-in-the-loop review for sensitive outputs — all logged for audit.
Which models and platforms do you work with?
We are vendor-neutral. We select models — commercial or open-source — per use case, data-residency, and cost, and deploy on the cloud you already use (AWS Bedrock, Azure OpenAI, Google Vertex AI, or self-hosted).
Do we need our own data scientists or ML team?
No. We deliver end to end — design, build, and run — and can hand over, co-run, or fully operate the solution. We also upskill your team along the way if you want to take it in-house.
How long until something is in production?
A focused, well-scoped use case typically reaches production in weeks, not months. We deliver iteratively so you see working software early and decide what to scale next based on real results.

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> Let's talk

Turn a GenAI idea into production

Tell us the use case you have in mind — we'll scope what it takes to design, build, and run it securely.