AI integration and RAG that answers from your data, for Georgia companies.
Retrieval-augmented generation (RAG) lets a language model answer from your own documents and systems instead of guessing. We connect it to the software Georgia companies already use, with permissions, citations and deletion in mind. Cloudsoft Industries LLC, a Delaware limited liability company. We serve clients worldwide; our engineering team works from Colombia (UTC-5).
Book a scoping call →What AI integration and RAG mean in practice
A general-purpose model has never seen your carrier agreements, your dispute playbooks, your production handbooks or your food-safety plans. RAG addresses that by retrieving relevant passages from your sources when someone asks a question and requiring the model to answer from them, with citations. Integration is the second half: placing that capability where people already work, such as the transport system, case-management tool, shared drive or internal portal, and connecting it to the systems that hold the truth. The result is an assistant that is useful because it is connected and dependable because it shows its sources. Projects start at $15,000, and we normally begin with the AI Readiness Sprint to choose the first sources and test answer quality.
Integration use cases across Georgia industries
These are illustrative scenarios for Georgia companies, not results from previous projects. Actual scope depends on your content, permissions and accuracy requirements.
| Industry | Typical use case | Sources and systems |
|---|---|---|
| Logistics and ports | Operations assistant for carrier terms, procedures and shipment status | Carrier agreements, procedures, shipment records |
| Payments and fintech | Analyst assistant for dispute rules and prior cases | Network rules, playbooks, case history |
| Film and media | Production search across contracts, permits and schedules | Contracts, permits, call sheets, shared drives |
| Healthcare | Staff assistant for approved policies and payer rules | Approved policies, payer guidelines, forms |
| Agriculture | Compliance assistant for specifications and certifications | Buyer specifications, certifications, supplier files |
Logistics and payments: answers with the clause attached
A dispatcher handling a delay needs to know what the carrier agreement says about detention, what the terminal's rules are and where the shipment stands right now. A retrieval layer over agreements and procedures, combined with live shipment records, can answer in one place with the clause cited. In payments, analysts handling disputes switch between network rules, internal playbooks and earlier cases. An assistant that searches those sources and cites them shortens the time to a first draft. Permissions matter in both: a customer's records should never appear in another customer's answers, so access rules are applied at retrieval time, not afterward.
Film, healthcare and agriculture: searching documents nobody can find
Production teams accumulate contracts, location agreements, permits and call sheets in shared drives that only the last coordinator understood. A search assistant over those files lets a new coordinator ask what was agreed with a location and get the clause. Healthcare administrators can use an assistant limited to approved internal policies and payer guidelines, which answers only from documents, cites them and declines to give clinical advice. Agricultural and food businesses can put buyer specifications, certifications and supplier files behind a single search, so a compliance question gets an answer with its source instead of a week of emails. Terms for handling any health data or unreleased content are agreed in writing before we connect to anything.
Where to start in Georgia
The best first project is usually the question your team asks most and answers worst. For a port-side operation that might be detention and demurrage terms across carriers; for a payments team, the evidence a particular dispute reason requires; for a production team, who approved what at a location. We pick one source set, define twenty to thirty real questions with expected answers, and measure the assistant against them before widening the scope. A small, well-measured first release earns trust with the people who will use it every day, and it gives you real numbers about quality before you invest in the next source.
Evaluation and monitoring
A demo is not a dependable system. We build a test set from the questions your staff really ask, measure whether the right passages come back and whether answers stay within the sources, and tune chunking, search and ranking before polishing the interface. Retrieval quality drifts as documents change, so AgentOps at $1,500/month monitors it after launch and flags questions that stop getting good answers. When no good source exists, the assistant says so rather than improvising.
Data protection and deletion
RAG systems copy content into search indexes, so every copy needs an owner and a deletion path. We trace each indexed passage to its source record so a deletion or correction can propagate, keep logs lean, and keep payment numbers out of indexes altogether. Systems run in your cloud accounts with your keys and least-privilege access. We hold no SOC 2 or other certification and never imply it; we document the architecture for your own security review. Our hours overlap your Eastern day, so design reviews and incident calls happen live. This is not legal advice. Contracts and invoicing in USD through Cloudsoft Industries LLC (Delaware). Clients own 100% of the code and IP once each milestone is paid. Code lives in the client's repositories from day one. Mutual NDA available.
Frequently asked questions
What is RAG, in plain terms?
Retrieval-augmented generation finds the relevant passages in your own content and asks the model to answer from them, with citations, instead of relying on what the model remembers.
Can the assistant respect who is allowed to see what?
Yes. Access rules are applied at retrieval time, so each user only receives answers built from content they are permitted to see.
Can it combine documents with live system data?
Yes, where the system has an API. An assistant can cite a contract clause and read the current shipment or case status in the same answer.
How do deletions reach the search index?
Each indexed passage is tied to its source record, so a deletion or correction at the source can propagate. We design this at the start and review it with your counsel.
How much does AI integration cost?
AI integration and RAG projects start at $15,000. The AI Readiness Sprint is $4,500 and AgentOps is $1,500/month.