AI integration services for the software you already run

An AI integration service connects an AI model to software you already use, so the AI can read your data and write results back. Typical examples are drafting replies inside a help desk, extracting fields from uploads or answering questions from your documents. SoftDoes builds these integrations through your APIs, in code you own.

LLM integration means calling a large language model, such as Claude, GPT or Gemini, from your own software through its API. The integration handles prompts, retries, caching, permissions and cost limits, so the model behaves like any other dependable service in your stack. It sits at the core of most AI integration projects.

Our AI integration services start at $4,000 for one AI feature in your software. A custom integration or MCP server also starts at $4,000. An AI agent connected to 1 or 2 systems starts at $7,000. Model usage and hosting are billed at cost on your own accounts. Our AI implementation cost guide shows typical ranges for larger rollouts.

Yes, in most cases. If your software has an API, a database we can reach or room for a backend service, we add the AI feature beside what exists. We build on a branch, test on your real data and release behind a flag. Nothing changes for your users until you approve the release.

It depends on the task, your data rules and cost. We test two or three models on your real examples and compare accuracy, speed and price per task before we choose. Many products use more than one model. SoftDoes is a Claude Partner Network member and an OpenAI Registered Partner, and we also build on Gemini.

Calls go through your own vendor accounts, under your contracts with each provider. We send only the fields a task needs, mask sensitive values where possible and log every request. Access follows your existing permissions, and keys stay in your secrets manager. For data that must stay in your cloud, see our private AI service.

Your team can, because the code, prompts, tests and documentation live in your repository. If you prefer us to run it, maintenance and support start at $500 a month. Support covers model updates, prompt fixes, cost monitoring and changes when a vendor retires a model.

It depends on the feature, the data and your release process. We set the integration's scope, price and schedule in a written plan before the build starts. Many teams begin with Project Discovery for $490, which is credited to the build. The plan also lists what we need from you, such as API access and test data.

Not when it is built for it. We stream answers as they generate, move long tasks to background jobs and cache repeated requests. Every AI call has a timeout and a fallback, so your app keeps working if a model is slow or down. We test speed on your real traffic before release.

We build a test set from your real examples and agree a pass mark before the build. The feature must meet it before release. Answers show their sources where possible, and a person approves outputs that carry risk. After launch we log answers, review errors and update prompts and tests.

Usually, yes. If we can reach the data through an API, a database or regular exports, we add the AI as a separate service beside the old system. If the code itself needs to change, see our AI code modernization service. We review the architecture first and tell you which route fits.

It adds model usage and hosting, billed at cost on your own accounts. We set cost limits and alerts per feature, and we cache repeated requests to keep usage down. Maintenance, if you want us to run it, starts at $500 a month. Compare these costs with the hours saved, as in the worked example above.

Yes, and it is the route we recommend. The first feature sets up the shared parts: model access, logging, permissions and cost controls. Each later feature reuses them, so it needs less new work. Your roadmap stays in your hands, because every part lives in your repository.

No. We design, build and document the integration, and your developers can maintain it from the repository. A product owner on your side approves the scope and each release. If you prefer, we run it for you from $500 a month, including model updates, prompt fixes and cost monitoring.

Any system with an API, a database we can reach or a regular file export. Common ones include PostgreSQL databases, REST APIs, webhooks, Salesforce and Zendesk. In one live build, AI files prior authorizations through Medicare's API. If a system has no API, we can often integrate through exports or a small connector service.