Claude API integration for applications that need sophisticated language reasoning.
Anthropic's Claude API for document analysis, content generation, multi-turn conversation, and the AI features that require high-quality instruction-following. Streaming responses, tool use, and the system prompt design that makes AI features reliable.
Application that needs AI capabilities beyond simple text completion — document analysis, structured output extraction, or multi-turn conversation with consistent behavior
Claude is the right choice for AI tasks that require:
Document analysis and long context. Claude 3 supports up to 200,000 tokens of context — entire codebases, long legal documents, or large PDF collections in a single API call. GPT-4 Turbo's 128,000 token context is smaller; for very long document analysis, Claude is the better model.
Instruction-following and safety. Claude is generally considered to follow complex, nuanced instructions more reliably than competing models. For applications where the AI needs to follow specific guidelines (don't make recommendations outside this scope, always cite sources), Claude's Constitutional AI training helps.
Structured output. Claude's tool use feature allows the model to return structured data by defining a tool schema. The model calls the tool with structured parameters — a reliable way to extract structured data from unstructured text.
The implementation decisions that determine whether AI features are reliable:
System prompt design. The system prompt establishes the model's behavior, tone, scope, and output format. A well-designed system prompt reduces output variance; a poor one produces inconsistent behavior that's hard to debug.
Streaming. Long AI responses block the UI if not streamed. The Vercel AI SDK's streamText and <AIStream> components handle streaming responses from Claude to the Next.js frontend.
Input validation. User-provided inputs that are passed to the AI prompt must be validated and sanitized. Prompt injection — where user input modifies the AI's instructions — is a real vulnerability.
Anthropic Claude API integration with streaming, tool use, system prompt design, and the input/output validation that makes AI features production-ready
API integration
`@anthropic-ai/sdk` setup. Model selection (claude-3-5-sonnet, claude-3-opus). API key management via environment variables.
Streaming responses
Vercel AI SDK `streamText` with Anthropic provider. `useChat` hook for client-side streaming display.
Tool use
Tool schema definition. Tool call parsing and execution. Multi-turn conversation with tool results.
Document analysis
Long-context prompts with document content. Chunking strategy for documents exceeding context limits.
Prompt templates
System prompt templates with Zod validation for dynamic inputs. Prompt versioning.
One honest number to start.
Fixed-scope, fixed-price. The number below is the starting point — final scope is built from your brief.
Anthropic Claude API integration with streaming, tool use, system prompt design, and the input/output validation that makes AI features production-ready
Three steps, every time.
The same repeatable engagement on every project. No surprises, no mystery, no billable ambiguity.
Brief & discovery.
We send you questions, then get on a call. Output: a written scope with every step, feature, and integration listed.
Build & ship.
Fixed schedule, weekly reviews. No scope creep unless you change the scope — and if you do, we reprice it transparently.
Warranty & retainer.
30-day warranty on every launch. Most clients stay on a monthly retainer for ongoing features and maintenance.
Why Fixed-Price Matters Here
AI feature scope is defined by the feature requirements and the model capabilities. Fixed price.
Questions, answered.
Claude Sonnet for: document analysis, long-context tasks, nuanced instruction-following. GPT-4 for: applications that need function calling with strict JSON schema, vision tasks (though Claude also supports vision), or OpenAI's ecosystem tools. Many applications use both — the best model for each task.
Validate and sanitize user inputs before including them in prompts. Separate user input from system instructions clearly in the prompt structure. Test adversarial inputs during development. The AI SDK's structured output features reduce injection risks compared to free-form prompt construction.
Part of the application build. AI-powered application from $25k. Fixed-price.
Tell Ryel about your project.
Describe what you’re building and what outcome you need. You’ll have a written, fixed-price scope within the week.