AI integration and RAG that answers from your data, for Washington companies.
Retrieval-augmented generation (RAG) lets a language model answer from your own documents and systems instead of guessing. We integrate it into the software Washington companies already run, 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 integration and RAG mean in practice
A general-purpose model has never read your engineering specifications, your clinical policies, your tariff schedules or your product catalog. RAG solves this by retrieving the relevant passages from your own sources at the moment a question is asked and instructing the model to answer only from them, with citations. Integration is the other half: wiring that capability into the places your people already work, such as the help desk, the intranet, a quality system or your product, and connecting it to the systems that hold the truth. The result is an assistant that is useful because it is connected and trustworthy because it shows where an answer came from. Projects start at $15,000, and we normally begin with an AI Readiness Sprint at $4,500.
Integration use cases for Washington industries
These are illustrative scenarios for Washington companies, not results from past projects. Real scope depends on your content, permissions and quality bar.
| Industry | Typical use case | Sources and systems |
|---|---|---|
| Cloud and software | Documentation and sales-engineering assistant | Docs, runbooks, tickets, past questionnaires |
| Aerospace | Specification and quality-procedure search | Procedures, work instructions, supplier records |
| Healthcare | Internal policy and protocol assistant | Approved policies, procedures, forms |
| Maritime logistics | Tariff, terminal-rule and procedure assistant | SOPs, carrier terms, shipment records |
| Retail and e-commerce | Product-knowledge and returns-policy assistant | Catalog, policy documents, order data |
Cloud and software: grounded answers for customers and sales teams
For software companies in the Seattle area, the strongest RAG projects face outward: a documentation assistant that cites the page it used, a support copilot that drafts replies from resolved tickets, or a sales-engineering tool that assembles technical answers from approved material. Retrieval quality decides success, so we build an evaluation set from real questions, measure whether the right passages come back and tune chunking, search and ranking before polishing the interface. Permissions matter as much as relevance: one customer's data must never surface in another's answers, so access rules are enforced at retrieval time, not afterward.
Aerospace and manufacturing: finding the right procedure fast
Shop-floor and quality teams lose time hunting through revision-controlled procedures, work instructions and supplier records. A RAG assistant can answer a question such as which inspection step applies to a part family and cite the exact controlled document and revision, so the person asking can verify it. The retrieval layer has to respect document status, showing only released revisions, and it has to log what was shown. Anything involving export-controlled technical data must be evaluated with your compliance team first because our engineers work from outside the United States.
Healthcare and harbor operations: sensitive and procedural content
Hospitals and clinics across Seattle and Spokane can use RAG for internal questions about approved policies, forms and procedures, with citations that point back to the source document and no clinical decisions made by the model. Washington's consumer health-data rules and HIPAA both shape the design, so handling terms are agreed in writing, identifiers are minimized and retrieval is limited by role. Port and logistics teams benefit from the same approach applied to terminal rules, tariffs and standard operating procedures, which are long, change often and are asked about constantly.
Keeping answers current and trustworthy
A RAG system is only as good as the content behind it, and in fast-moving Washington industries that content changes weekly. We set up ingestion so that new and revised documents are indexed on a schedule, retired documents are removed and each answer shows the date of its source. Evaluation does not stop at launch: a fixed set of real questions is re-run after every content or model change, and a drop in quality raises an alert before your users notice. That ongoing care is what AgentOps covers.
Security, permissions and ownership
Integration work is where security is decided. We enforce permissions at retrieval time, keep embeddings and logs in your cloud accounts, set retention limits and design deletion so it reaches indexes and caches. We hold no SOC 2 or other certification and say so; we document the controls your security review asks for. Projects start at $15,000, the AI Readiness Sprint is $4,500 and AgentOps is $1,500/month. 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 documents and gives them to a language model so it answers from them, with citations, instead of relying on general knowledge.
Can our data stay in our own cloud?
Yes. We build inside your cloud accounts and repositories, keep indexes and logs there and set retention rules, so the system and its data remain under your control.
How do you prevent one user seeing another's data?
Permissions are enforced when documents are retrieved, using your existing access rules, so the model never receives content the person asking is not allowed to see.
How do you measure answer quality?
We assemble an evaluation set from real questions, track whether the correct sources are retrieved and whether answers stay faithful to them, and re-run that set after every change.
What 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.