→ LLM integration services
LLM integration services for products that have to run in production
The model call is 10% of the work. We handle the other 90%. Caching, structured outputs, function calling, prompt versioning, eval, cost ceilings, fallback chains.
Overview
How we approach this work.
LLM integration services from Resser cover the engineering around the model call: the structured-output schemas, the eval suite, the prompt versioning, the cost telemetry, the retry logic, the fallback chains, and the observability that turn a prototype into a production feature.
We integrate Anthropic, OpenAI, Google, and open-weights LLMs into web apps, mobile apps, backend services, and existing enterprise software. Most engagements add an LLM-powered feature inside a product the customer already ships.
Most agencies sell 'GPT integration' as a single API call. The single call is the easy part. The hard parts are the prompt versioning, the eval that catches regressions, the cost ceiling that prevents a runaway loop, and the fallback when the primary provider rate-limits at 2am.
What we build
Concrete deliverables.
Production LLM features inside existing software
Add a summarizer, generator, extractor, or copilot into the product you already ship.
Structured outputs against your schema
JSON schema, Pydantic, zod. Every LLM call returns typed data your downstream code can trust.
Function calling and tool use
LLM-driven actions against your real APIs, with strict tool schemas and dry-run safety.
Streaming UIs
Token-by-token streaming, tool-call visualization, multi-turn conversation state. Vercel AI SDK end-to-end.
Cost and rate-limit guardrails
Per-request cost cap, per-session cap, per-cohort alerting, fallback to a secondary model on rate limit.
Eval and prompt versioning infrastructure
Every prompt change runs through the eval suite in CI. Rollback is a one-line change.
Stack
What we build with.
Model providers
Anthropic (Claude Haiku, Sonnet, Opus), OpenAI (GPT-4o, o-series, GPT-4.1), Google (Gemini), AWS Bedrock, Azure OpenAI Service, GCP Vertex AI.
Open-weights via vLLM
Llama 3, Mistral, Mixtral, Qwen 2.5, DeepSeek, Phi, Gemma. For private deployments where the model must stay inside your perimeter.
Frameworks and SDKs
Vercel AI SDK, Anthropic SDK, OpenAI SDK directly, LangChain / LangGraph when the orchestration is complex enough to justify it, Pydantic AI for type-safe Python.
Observability and eval
Helicone for cost and latency, LangSmith or Braintrust for eval, Promptfoo for CI-driven test suites, custom telemetry in Postgres or Clickhouse.
Outcomes
What we ship.
B2B SaaS feature: prompt caching cut token spend significantly with no measurable quality drop on the eval set.
Customer-support summarization: streaming UI with structured outputs deployed end-to-end in a few weeks.
Document extraction at scale: fallback chain across providers (Claude / GPT-4o / on-prem Llama) kept the feature highly available over a 90-day window.
References with names available after a scoping call.
Related services
Other places this work shows up.
FAQ
Frequently asked.
Which LLM provider should we use?
Anthropic Claude Sonnet for reasoning-heavy multi-step work. OpenAI GPT-4o or o-series for structured extraction at scale. Open-weights for sovereignty. We benchmark on your data in discovery week before locking the choice.
Do you handle prompt versioning and rollback?
Yes. Every prompt is versioned in the codebase, runs through an eval suite in CI, and rollback is a one-line change. A hotfix on a Wednesday should not be a permanent change.
What is the typical timeline for an LLM integration?
Discovery week first. Then 2-3 weeks for a working integration in your environment with eval live. Then 2-4 weeks of hardening (cost telemetry, fallback chains, observability). Most features reach production in 5-8 weeks.
How much does an LLM integration cost?
A small LLM-integration feature into existing software starts at €10,000-€25,000. A multi-feature LLM integration with eval, observability, and structured outputs sits in the €25,000-€60,000 range.
Want to scope this for your project?
Fill the project-estimate form. We reply within one business day with a preliminary scope and a rough budget bracket.