HOUSTON, Texas – Centric, a Houston-headquartered digital transformation and marketing agency, is helping US enterprises move generative AI out of the pilot stage and into daily work by building AI assistants that answer from a company’s own policies, manuals, contracts and records.

Many organizations have tested public chatbots and found the same limits. The tools do not know internal procedures, they can give confident answers that are wrong, and security teams are often unwilling to send sensitive documents to a public service. As a result, years of company knowledge stay locked in shared drives and document libraries that employees struggle to search.

As a generative AI development company, Centric designs and builds systems that connect large language models to an organization’s approved content, so answers are grounded in the company’s own information rather than general internet data.

What are generative AI knowledge systems?

A generative AI knowledge system is an assistant that searches an organization’s approved documents and data, then writes an answer based on what it finds. The most common approach is retrieval-augmented generation, or RAG. Instead of relying only on what a model learned during training, a RAG system first retrieves relevant passages from trusted sources and then uses them to produce a response.

What Centric builds

Centric’s generative AI and knowledge systems work covers:

• LLM solutions built on models from OpenAI, Anthropic, Google and Microsoft
• RAG pipelines that connect models to approved company content
• Knowledge assistants that help employees find answers in policies, SOPs and manuals
• Document summarization and extraction for long, complex files
• Knowledge graphs that map how people, products, assets and documents relate

Deployment options include private, hybrid and air-gapped environments, which matters for organizations where data residency or security rules block the use of public AI tools.

Who it is for

Generative AI knowledge systems are most useful for organizations that:

• Hold large volumes of policies, procedures, manuals or contracts that staff rarely read in full
• Work in regulated industries where answers must be traceable to a source
• Have knowledge spread across siloed systems and teams
• Have paused AI projects over concerns about inaccurate answers or data exposure

From pilot to production

Centric’s broader enterprise generative AI solutions sit within an artificial intelligence practice that also covers AI strategy, conversational AI and Copilot, intelligent automation, predictive AI, computer vision and AI deployment. Engagements typically begin with a readiness assessment and use-case prioritization, so organizations invest first in the use cases most likely to deliver measurable value.

This step-by-step approach is designed for companies that have run several AI experiments but have not yet moved one into governed, everyday use.

Frequently asked questions

How is a RAG assistant different from a public chatbot?

A RAG assistant answers from an organization’s own approved content and can point to the source documents it used. A public chatbot answers from general training data and has no access to internal knowledge.

Can generative AI run without sending data to a public service?

Yes. Systems can be deployed in private, hybrid or air-gapped environments, depending on an organization’s security and data residency needs.

About Centric

Centric is a digital transformation and marketing agency headquartered in Houston, Texas, with a presence in Dubai and Riyadh. The company provides services across artificial intelligence, data and analytics, Microsoft cloud, SharePoint consulting, web and mobile development, SEO and digital marketing, and reports more than 2,000 projects delivered. Learn more at centricdxb.com.