ai / llm-integration

LLM Integration

Add AI features to your product the right way. We integrate AWS Bedrock, OpenAI, Anthropic and OpenRouter behind a clean model layer, with structured output your code can trust and fallbacks for when a provider has a bad day.

Add AI to Your ProductAll AI services
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Extract the vendor, total and due date from this invoice.

llm.generate({ schema: InvoiceSchema })✓ valid JSON
zod.parse(InvoiceSchema)✓ passed

{ "vendor": "Acme Supplies", "total": 1240.50, "dueDate": "2026-11-01" }

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Calling an API Is Easy. Shipping It Is Not.

A demo needs one prompt and one API key. A product feature needs reliable output, predictable cost and a plan for outages and model changes.

Free-text responses that break parsers in production
Code tied to one provider and one model version
No retries or fallbacks when a provider rate-limits or fails
Costs that grow with usage and nobody tracks
capabilities

What Good Integration Looks Like

LLM features engineered like the rest of your backend

Structured Output

Responses validated against Zod schemas before your code touches them.

Provider Freedom

One model layer over Bedrock, OpenAI, Anthropic and OpenRouter. Switch per feature.

Resilience

Retries, timeouts and fallback models keep features working during outages.

Streaming UX

Responses stream to the UI so features feel fast, even on long outputs.

graph

How We Integrate LLMs

  1. node: pick_the_right_model

    Pick the Right Model

    Quality, Speed and Cost per Feature

    We benchmark candidate models on your real inputs, then choose per feature instead of using one model for everything.

    • Side-by-side evals on your data
    • Cost per request estimated up front
    • Latency measured, not assumed
    • Data residency and privacy checked
  2. node: build_the_model_layer

    Build the Model Layer

    Typed, Testable, Swappable

    A small TypeScript layer handles prompts, schemas, retries, fallbacks and streaming, so product code stays simple.

    • Prompts versioned with the code
    • Zod schemas for every output
    • Fallback chains across providers
    • Streaming to web and mobile clients
  3. node: operate_it

    Operate It

    Visibility From the First Request

    Every call is traced with tokens and cost, so you can tune prompts and models with data.

    • Tracing with LangSmith or Langfuse
    • Token and cost tracking per feature
    • Alerts on errors and spend
    • Regression evals for prompt changes
tools

Providers and Tools We Use

Chosen per feature, never locked in

"name": "AWS Bedrock",
"description": Managed access to leading models inside your AWS account, with your existing IAM and networking.
"name": "OpenAI",
"description": Strong general-purpose and structured-output models for many product features.
"name": "Anthropic",
"description": Claude models for long context, careful reasoning and tool use.
"name": "OpenRouter",
"description": One API across many models, useful for comparing and routing between them.
"name": "LangChain",
"description": Model abstractions, structured output helpers and integrations.
"name": "Zod",
"description": Runtime validation that turns model output into typed data.
trace

Shipping an LLM Feature

  1. 01 Define the Feature

    Inputs, outputs, quality bar and budget per request.

  2. 02 Model Bake-Off

    Compare models on real examples for quality, speed and cost.

  3. 03 Schema and Prompt

    Design the output schema and the prompt that fills it.

  4. 04 Model Layer

    Implement retries, fallbacks, streaming and validation.

  5. 05 Evals and Tracing

    Add regression tests and production tracing.

  6. 06 Launch and Tune

    Ship behind a flag, watch traces and cost, and iterate.

evals

What You Can Count On

Standards for every LLM feature we ship

PASS
Validated
Output
schema-checked before it reaches your code
PASS
Swappable
Models
change providers without rewrites
PASS
Tracked
Cost
tokens and spend per feature
PASS
Resilient
Calls
retries and fallbacks built in

Ready to Ship AI Features Users Trust?

Tell us the feature you have in mind. We will help you pick the model, design the output and ship it with cost and quality under control.

Describe the task you want AI to take off your plate…Discuss Your AI Feature