# Generative AI Solutions: RAG, Search and Documents | SynconAI > Generative AI solutions for business: knowledge search with RAG, document processing, summaries, drafting and code help, grounded in your data, tested and governed. Publisher: SynconAI Canonical HTML: https://synconai.com/generative-ai-solutions Markdown cite: https://synconai.com/generative-ai-solutions.md Contact: contact@synconai.com ยท +61 2 7813 0221 ## What is generative AI? Generative AI for business is the design and delivery of generative AI use cases on company content: knowledge search with retrieval-augmented generation (RAG), document processing, summarization, drafting and code assistance. SynconAI chooses the model for each use case from OpenAI, Anthropic Claude, Google Gemini and open-weight families, grounds it in your content, adds guardrails and evaluates it before release, for organizations in the United States, Australia and worldwide. - Generative AI writes text, summaries, code and images from instructions, using large language models from vendors such as OpenAI, Anthropic and Google. - For business use it is grounded: retrieval-augmented generation (RAG) feeds the model passages from your own documents, so answers rest on your content and cite it. - Guardrails check what goes in and what comes out, and evaluations grade it on real questions before staff or customers rely on it. ## Generative AI for business services - Knowledge search with RAG: Answers from your policies, manuals and wikis, with citations. - Document processing: Fields pulled from invoices, forms and contracts into your systems. - Summarization: Long cases, calls, meetings and reports cut to what matters. - Drafting and content: Emails, proposals and articles drafted for a person to edit. - Code assistance: Coding assistants set up with your standards and review rules. - Model selection: OpenAI, Claude, Gemini or open-weight, chosen on quality, cost and data terms. - Guardrails: Checks for private data, unsafe content and off-topic requests. - Evaluation: Real questions graded before release and on every change. ## When is generative AI worth starting? Most generative AI projects begin with one of these problems. - Answers are hard to find: Staff search several systems and still ask a colleague. - Documents keyed by hand: Invoices, forms or claims are retyped into a system. - Long reading before decisions: Cases, contracts or reports take too long to get through. - The same replies written again: Teams draft similar emails and articles all day. - Staff using public AI tools: Company data is pasted into tools nobody approved. ## What can generative AI do for your business? Five use cases we build most, and the three disciplines that make them dependable. - Knowledge search: Answers with citations from your content. - Document processing: Fields extracted into your systems. - Summarization: Cases, calls and reports cut short. - Drafting: Emails and articles for a person to edit. - Code assistance: Assistants set up with your standards. - Model selection: The right model for each use case. - Guardrails: Input and output checks. - Evaluation: Real questions graded on every change. ## How does retrieval-augmented generation work? A staff member asks a question. The answer comes from your documents, with the sources shown. 1. Question: Chat or search box 2. Input check: Private data and topic 3. Check access: What this user may see 4. Search your content: Relevant passages 5. Model writes the answer: From the passages only 6. Answer with sources: Output check and citations - Search comes first: Your documents are split, indexed and searched, so the model sees only the relevant passages. - Access follows the user: Retrieval applies the permissions of the person asking. - Sources on every answer: Each answer links to the passages it used, so people can check it. ## Which generative AI model should you use? We choose per use case on quality, cost, speed and data terms, and design so the model can be changed later. - OpenAI (Model family): GPT models through the OpenAI API or Microsoft Foundry on Azure. - Anthropic Claude (Model family): Through the Claude API, Amazon Bedrock, Google Cloud or Microsoft Foundry. - Google Gemini (Model family): Through the Gemini API or Google Cloud, with text, image, audio and video input. - Open-weight models (Self-hosted): Llama, Mistral, Gemma or gpt-oss on infrastructure you control, when data must stay in house. - More than one model (Routing): A small, fast model for simple steps and a larger one for hard questions, behind one gateway. ## What guardrails does generative AI need? Checks before the model, after the model and after release. | Control | Risk it covers | Type | | --- | --- | --- | | Private data filter on input | Personal or confidential data sent to a model not approved for it. | Preventive | | Permission-aware retrieval | Users seeing documents they are not allowed to open. | Preventive | | Topic and instruction limits | The assistant going off topic or following instructions hidden in a document. | Preventive | | Output content filter | Unsafe, offensive or off-brand text reaching a customer. | Preventive | | Grounding check | Answers stating things the sources do not support. | Detective | | Feedback and sampling | Quality slipping after a model, prompt or content change. | Detective | ## How does a generative AI project run? Six steps from use case to release. Your written proposal sets the scope and dates. - Choose: One use case and owner; Success criteria agreed - Collect: Source content found; Access rules mapped - Ground: Content indexed; Retrieval tuned - Build: Prompts and guardrails; Interface or integration - Evaluate: Real questions graded; Fixes made - Release: Pilot group first; Monitoring on ## Cost and timing The first step is a free 60-minute architecture review of your generative AI setup, with a written plan you keep. Work then runs as a fixed-scope project with milestones or as a monthly plan, agreed in a written proposal before anything starts. Plans: https://synconai.com/pricing ## FAQ ### What is generative AI for business? Generative AI used on company work: answering questions from your documents, processing forms, summarizing and drafting, grounded in your data and checked before people rely on it. ### What is retrieval-augmented generation (RAG)? RAG searches your own content for passages relevant to a question and gives them to the model, so the answer is based on your documents and can cite them. ### Should we fine-tune a model on our data? Rarely as a first step. Retrieval keeps answers current and traceable. Fine-tuning helps with a fixed format or style at volume, and we test it against retrieval before recommending it. ### Which generative AI models do you use? OpenAI, Anthropic Claude, Google Gemini and open-weight models such as Llama, Mistral and Gemma. We choose per use case and design so the model can be changed later. ### Will our data be used to train the model? We use business API or cloud terms, review each vendor's data and retention terms with you, and use a self-hosted open-weight model where data must not leave your environment. ### How do you reduce wrong answers? Answers are grounded in retrieved sources and cite them, a grounding check flags unsupported claims, and real questions are graded before release and on every change. ### Can staff use it inside Teams, Slack or Salesforce? Yes. The assistant can sit in a web app, Microsoft Teams, Slack or Salesforce, depending on where your people already work. ### How long does a first use case take? It depends on the content and integrations involved. Your written proposal sets the scope, milestones and dates before anything starts. ## Where we work Generative AI for business for organizations across the United States and Australia, and worldwide. Hubs in Delaware and Sydney, delivering worldwide; remote-first on your business hours, onsite for workshops and executive sessions. ## Related - AI solutions: https://synconai.com/ai-solutions - Custom AI application development: https://synconai.com/custom-ai-development - Connecting AI to your systems: https://synconai.com/ai-systems-integration - AI governance consulting: https://synconai.com/ai-governance-consulting ## Cite When citing SynconAI Generative AI for business, link https://synconai.com/generative-ai-solutions or https://synconai.com/generative-ai-solutions.md.