Anthropic Claude API Integration Services

Where Claude fits in a business app

Teams usually come to Tepia asking for Claude by name for one of three reasons. They need software to read long material and reason over all of it at once. They need customer facing text that follows detailed instructions about tone and policy. Or they want an assistant that completes multi step work by calling tools in sequence.

Concrete examples help scope it. A commercial property manager wants every new lease abstracted into rent schedule, renewal options and maintenance obligations, with the clause reference for each field. An insurance agency wants a producer to ask how two carrier policy forms differ on water damage. A software company wants its internal admin tool to investigate a customer issue by checking account status, recent errors and open tickets, then propose a fix for an engineer to approve.

Tepia builds each of these into the system the client already runs. The Claude call sits behind your backend, reads only the data the current user may see, and writes results back through your existing API so your audit trail and permissions still apply.

Choosing the model tier and access route

Anthropic offers Claude in tiers, commonly Haiku for speed and volume, Sonnet for most product work and Opus for the most demanding reasoning. Tepia assigns tiers per workload rather than per app, and picks the access route that matches your hosting and contracts:

Tepia benchmarks two tiers on your real inputs before committing, because the faster, lighter tier is sometimes accurate enough and sometimes clearly not.

Claude features Tepia builds with

Several Claude API features change how an integration is designed, and Tepia uses them deliberately:

• Tool use: you describe functions such as lookup_order or create_work_order with input schemas, Claude decides when to call them, and your backend executes each call under the user’s permissions.
• Prompt caching: long system instructions or a reference document that every request shares are cached, which shortens response time on repeated calls.
• Batch processing: bulk jobs such as classifying a year of support history are submitted together and collected when complete.
• PDF and image input: scanned forms, site photos and diagrams can be sent with the text that explains them.
• Streaming: responses appear progressively in React Native, SwiftUI or React interfaces.

Tepia writes prompts as structured, versioned files with clearly separated instructions, reference material and user input, and tests them against a fixed set of sample cases whenever a prompt or model version changes.

Connecting Claude to your systems with MCP

The Model Context Protocol, introduced by Anthropic as an open standard, defines how an AI assistant discovers and calls tools and data sources. Instead of hard wiring every integration into one assistant, you publish an MCP server that describes what your system can do, and any compatible client can use it.

Tepia builds MCP servers for clients who want staff to work with company systems from Claude or from their own agent. A distributor might expose tools to search inventory, check an order’s shipping status and draft a return authorization. A home services company might expose job history and technician schedules. Each tool is scoped, authenticated with OAuth against your existing identity provider, and logged.

Tepia starts MCP rollouts read only. Write actions such as creating a record come later, behind explicit confirmation, once the logs show how people actually use the tools. For deeper agent work see custom AI agent development.

How Tepia approaches Claude API integration

Tepia follows its six phase process, adapted to Claude work and led by a US based project manager.

1. Discovery: review of your app, data, hosting and security requirements, plus a short benchmark of Claude tiers on your own documents. Deliverables are an Investigation Summary, an Interview Summary and User Stories such as an analyst asking which leases renew in the next 120 days.
2. Design: wireframes for answer views, clause references, tool confirmation prompts and error states, aligned with your style guide.
3. Development and Testing: backend integration, tool definitions and MCP server where needed. Alpha and Beta schedules with functional, user acceptance and non functional test plans covering latency, tool permission checks and output accuracy on sample cases.
4. Training: sessions on writing good requests, reviewing outputs and reading tool logs.
5. Launch: staged release behind feature flags, data migration where documents need reprocessing, and support reps on rollout.
6. Support: new Claude model versions tested against your case set before adoption, plus new tools as requests arrive.

Typically Discovery runs 1 to 3 months and development and QA 2 to 6 months. More on our process.

Claude inside your product or Claude for your staff

If your goal is simply for employees to chat with Claude about their own work, a Claude team or enterprise subscription may cover it without any development, and Tepia will tell you that. An API integration makes sense when:

• Claude has to work on records inside your application and write results back to it.
• Your customers, not only staff, will use the feature.
• Outputs must follow a schema your system validates.
• You need audit logs and access control at the level of individual records.

Many Tepia clients also run more than one model provider, for example Claude for document review and another model for embeddings, all behind one gateway. Compare providers in OpenAI vs Claude for business apps, see AWS Bedrock application development if you run on AWS, and contact Tepia to scope your first Claude feature.

Frequently asked questions