# AI Integration Services for SaaS Apps > Production-focused AI integration for existing SaaS applications, product features, data, APIs, and operational workflows. - Canonical: https://haseebeqx.com/services/ai-integration-services/ - Published: 2026-08-20 [← Services / AI integration](/services) Add AI to the software you already use # AI integration services *for SaaS apps.* I help SaaS teams add useful AI capabilities to the applications and workflows they already operate—connecting models to real product data, permissions, APIs, business rules, and human review without starting with a rewrite. [Tell me what you need →](/contact-me/) [See what I can build ↓](#capabilities) Service briefAI / SaaS You have A SaaS app or work process We start with One clear AI feature I connect AI, your data, APIs, and tools I include Tests, access rules, and human review Ways to work Trial project, fixed project, or contract Before I start, we agree on what I will build, what I need access to, how long it should take, and what it will cost. 01 / What I can build ## Add AI without replacing *your whole app.* Calling an AI service is the easy part. The feature also needs to use the right data, follow your rules, work well for users, and handle errors safely. What I build 01 ### AI service connections Connect your app to OpenAI, Anthropic, or another AI provider. I keep the connection in one clear part of your code so it is easy to change later. What I build 02 ### Features your users can see Add AI search, writing help, document summaries, data extraction, sorting, or a simple assistant for one clear job. What I build 03 ### Answers from your data Let AI find and use approved app data or documents. Users only see information they already have permission to view. What I build 04 ### Help with repeat work Connect AI to your current tools and APIs. Check its output and ask a person to approve any important action. 02 / Relevant experience ## AI work I have done *in real products.* I have built AI and speech features for education, financial compliance, meetings, and research. Here are examples of the users, tools, and work involved. Financial complianceRuby + AI ### Compliance checks with AI help Built tools for employee compliance and vendor checks. AI was added to work that had business rules, sensitive data, and review steps. - Employee compliance - RAG - Human review in the workflow Nonprofit educationSpeech to text ### Pronunciation and reading tools Connected speech-to-text tools to pronunciation checks and reading features for a learning platform used by underserved students. - Spoken-word input - Pronunciation checks - Reading support Online meetingsSpeech to text ### Meeting transcription Built meeting transcription that worked across the tools teams already used instead of making them change how they met. - Google Meet - Zoom - Microsoft Teams Research workflowAI tools ### AI-assisted eligibility filtering Built a tool that fetches data from multiple sources and verifies claims in each application - Source discovery - Result filtering - Structured reports A good first project ## One useful feature. - Choose who will use it and what it should do - List the data, access rules, APIs, and tools it needs - Choose and connect the right AI service - Make the result work inside your app - Test common cases, errors, and human review - Write down how it works and where it can fail What we do not need ## A full AI rewrite. - Replacing your current app - Building many unrelated AI ideas at once - Training a new AI model from zero - Letting AI take important actions on its own - Making promises no AI system can guarantee - Adding servers or tools the first feature does not need 03 / Delivery process ## Start small. *Build it into your real app.* The first version does one clear job. We test it with realistic examples, then put it into the app your team already runs. 1. 01 ### Choose the job Agree on who will use the feature, what problem it fixes, what goes in, and what a good result looks like. 2. 02 ### Plan the safe path Decide what data AI can use, which service to use, what to test, when a person checks the result, and what happens if it fails. 3. 03 ### Build it Add the feature to your current app and connect it to the data, APIs, and tools it needs. 4. 04 ### Test and hand over Try it with realistic examples, fix weak spots, write down its limits, and show your team how it works. A deliberate constraint ## Not every feature needs AI. If normal code, a simple API, or a small process change would work better, I will say so. The goal is to solve a real problem, not to add AI just because it is popular. 04 / FAQ ## AI integration *questions.* What does AI integration mean? It means adding an AI feature to software you already use. I connect the AI to the right data, rules, APIs, and screens. I also test failures and add human checks where they matter. Do we need to rebuild our SaaS app? Usually not. I can add one feature at a time while your current app keeps running. The best approach depends on your code, data, and hosting setup. What can you add to our product? I can add AI search, writing help, document summaries, data extraction, sorting, support tools, speech features, and repeatable work steps. First, we check that AI is a good fit for the job. Can it work with our current tools? Yes, if the tools have an API or another safe way to connect. The feature can use events and data from your app and other services. We keep access checks and human approval where needed. Do you only work with Rails apps? Rails is the stack I know best, but I can work with other apps too. We can check your setup, the tools you use, and the one feature you want to add. Have a SaaS app and one clear AI idea? ## Keep your app. *Add one useful feature.* [Tell me about it ↗](/contact-me/)