Service Claude API integration · Opus + Sonnet + Haiku · UK

Claude API integration that reads the whole doc. not just the first page.

Claude API integration for UK SaaS, fintech, and legal-tech teams. Opus 4.8, Sonnet 4.6, and Haiku 4.5 behave like three specialists — wired behind one gateway with 200K context, prompt caching, MCP tool-use, evals, and a config-swap to GPT-5 when a task suits it.

Send a 5-line brief Provider-agnostic? Start here

24hreply, from a senior

100+projects shipped since 2019

Senioronly, on the spine

(Why teams pick Claude)

The Claude integration your senior engineer would have written. Twenty-eight built, the same gateway shape every time.

Claude is the model teams reach for when tone, long context, and tool-use reliability matter. We make it cheap enough to run at scale and portable enough to never lock you in.

Send a 5-line brief

0+

Claude API integrations shipped to UK clients since 2023/01

0%

Median prompt-cache hit rate after caching is configured correctly/02

0K

Token context window we routinely build against/03

The story every legal-tech CTO knows60-page contract · chunked · missed the cross-reference

The old model read the contract in chunks. It missed the cross-reference.

01

A UK legal-tech reviewed 400-plus vendor contracts a quarter against a playbook. Their first integration chunked each document into 8K windows, summarised each, and stitched the results. It worked, until a clause on page 4 referenced a definition on page 97, and the stitched summary missed it. A customer signed on a misread. That’s the kind of bug a chunking architecture creates.

02

We rebuilt it on Claude Opus 4.8 with the full 200K context window, reading each contract in one shot and prompt caching it so ten questions cost a fraction of the first. The whole document in context. Cross-references resolved. Senior lawyer time dropped 65%, and a new tier added £180K a year in revenue.

03

This page is for the team that needs the whole document understood, not the first page summarised. Claude wasn’t built for everything. It was built for three things: long-document reasoning, careful tone, and tool-use you can trust. That’s the integration we build.

Long-context first since 2023

Claude API integration · pick the smallest tier that hits the eval

Three Claude tiers.
Three different specialists.

Production almost never runs on just one. Routed correctly, you get Opus accuracy with Haiku economics on most calls. Open any row.

The reasoning ceiling. Slower, pricier, worth it for the work no other tier can finish: complex agents, code review, long contracts, multi-step planning. We route only what truly needs it here.

The right balance of cost, capability, and latency. It gets the writing voice right, follows instructions cleanly, and handles tool-use reliably. Chatbots, RAG, document Q&A, content, tool-use agents: most product-facing work lands here.

Fast and cheap, run hundreds of times a minute without breaking your budget. Classification, routing, extraction, the high-volume majority. Where the cost savings live, fast enough for real-time UX.

What we wire from the Claude platform

Six capabilities, one discipline

Each one wired behind the same gateway, budget caps, and eval gold set. No special-casing, no bypass.

Wire your feature

Context

200K context window

Whole contracts, codebases, knowledge bases in one prompt. No chunking.

Caching

Prompt caching

Cache the long context once. Ask many questions. Up to 90% cheaper.

Tools

Native tool-use

Reliable function calling. Schema-validated. Wired to your real systems.

Vision

Document + image understanding

Scanned PDFs, charts, tables, screenshots. Read in the 200K window.

MCP

Model Context Protocol

Write the tool once, any model that speaks MCP can call it. 12 MCP servers built for clients in 2025.

Structured

Schema-bound outputs

Tool-use enforces structure. Valid JSON or a retry. No regex parsing.

WHY TEAMS SIGN

Claude’s judgement, without Anthropic owning your runtime

Five things that turn a single-provider feature into a defensible, portable one. Click to open.

REASON(01)

The full 200K window

The whole document in context. No chunking, no stitched summaries, no missed cross-references.

200K contextNo chunkingWhole-docCodebase-aware

The full 200K window

REASON(02)

Three-tier routing on every project

Haiku, Sonnet, Opus, routed per task with a 90% prompt-cache hit. Median 5.2× cost reduction, same accuracy.

5.2× cheaper90% cache hitPer-tenant budgetsRAG-cheap

Three-tier routing on every project

REASON(03)

MCP servers built in-house

Claude’s tool-use is reliable. We wire it through MCP so tools are defined once and used everywhere. 12 MCP servers built for clients in 2025.

12 MCP serversTool-useSchema-validatedReusable tools

MCP servers built in-house

REASON(04)

Provider-agnostic gateway

Use Claude for tone + reasoning. Swap to GPT-5 or Gemini in config when a task calls for it.

GatewayNo lock-inConfig swapEval-verified

Provider-agnostic gateway

REASON(05)

Eval gold set + Bedrock option

CI-gated evals on every release. Run Claude via AWS Bedrock in your VPC for regulated data.

Eval-gated CIAWS BedrockVPCDPA

Eval gold set + Bedrock option

The eight Claude-integration pains we hear in every audit

The pain. The day-1 architecture answer.

Each one decides whether your Claude feature ships, scales, and stays inside budget.

01
The chunking missDay-1 architecture
“We chunk long documents and the model misses cross-references between pages.”
Full 200K context + prompt caching. The whole document in context. Cross-references resolved. Cache it once, ask many questions at a 90% hit rate. Median saving: £10K a year on a 50K-calls-a-month workload.
02
Runaway billDay-1 architecture
“We ran everything on Opus and the bill is enormous.”
Per-task routing across Opus / Sonnet / Haiku. Haiku for the 60%, Sonnet for 35%, Opus for the 5% that needs it. Same accuracy, a fraction of the cost. Median 5.2× cheaper, verified against your gold set.
03
Tool-use reliabilityDay-1 architecture
“The model calls our tools with the wrong arguments and we can’t trust it.”
Native tool-use + schema validation + MCP. Claude’s tool-use is reliable, and we validate every tool call against a schema. Tools defined once via MCP, reused across features. 12 MCP servers built for clients in 2025.
04
Provider lock-inDay-1 architecture
“We’re 100% Claude. If Anthropic changes pricing we have no leverage.”
Provider-agnostic gateway. Use Claude where it wins. Swap to GPT-5 or Gemini or self-hosted Llama in config. Verified against your gold set before cutover.
05
Rate-limit outageDay-1 architecture
“We hit Anthropic’s rate limit at peak and the feature died.”
Backoff + queue + fallback provider. Exponential backoff, request queue, and automatic fallback to a second provider when Claude 429s. No single point of failure.
06
Data privacyDay-1 architecture
“Will Anthropic train on our customer data?”
Zero-retention + PII redaction + Bedrock option. Anthropic doesn’t train on API data by default. PII redaction at the gateway. For regulated data, run Claude via AWS Bedrock in your VPC. DPA before week one.
07
The silent regressionDay-1 architecture
“We tweaked a system prompt and quality dropped. We don’t know by how much.”
Versioned prompts + eval-gated CI. Prompts in your repo, versioned. Every PR runs the gold set. Drop more than 5% and the deploy is blocked.
08
Vision + doc complexityDay-1 architecture
“We need to read scanned PDFs and images and the plumbing is fiddly.”
Claude vision + document understanding. Claude reads scanned PDFs, images, charts, tables in the 200K window. Wired with the same gateway, budget, and eval discipline.

Claude integration tech stack · MERN + Python + AWS Bedrock

The stack we ship every Claude build on.

Claude’s models behind a gateway, evals on every release, AWS + Bedrock underneath.

T1

What we ship every Claude build on

gateway + evals

Claude Opus 4.8Claude Sonnet 4.6Claude Haiku 4.5MCPNode.js + ExpressPythonMongoDBTypeScriptMixpanelSentryLangSmithGitHub Actions

T2

For the fallback + the brief that needs it

reach when needed

OpenAI GPT-5Google GeminiLlama / MixtralPinecone / pgvectorLangChain / LangGraphFastAPI

T3

The cloud + infra

AWS Bedrock-default

AWSAWS BedrockAWS LambdaKubernetes (EKS)DockerRedisApache KafkaS3 + CloudFrontTerraformDatadogWebSocketsGoogle Vertex AI

PROOF

Claude in production, real outcomes

A UK legal-tech’s contract-review tool, rebuilt on the full 200K window with prompt caching: 400 contracts a quarter, 70% straight-through, senior lawyer time down 65%, a new tier adding £180K a year. What clients say six months in.

100% would refer us

Edmund T. Founder · UK LegalTech

Senior lawyer time dropped 65% in the first quarter. The 200K window means contracts read in one pass. No chunking, no missed cross-references.

01 / 06

Claude API integration · honest answers

What CTOs actually ask before signing

Pain-first, soft-second.

Most production AI products end up using both, routed per task. Claude for long-document reasoning, careful tone, and tool-use: contract review, brand-safe support, codebase-aware agents, anything needing the 200K window. GPT-5 for vision, voice, and image generation. We build a gateway so you don’t have to pick a forever-favourite, and we’ll be honest in audit week about which model wins each task.

Route per task. Haiku 4.5 for the 65% of classification/routing/extraction, Sonnet 4.6 for default reasoning and product-facing work, Opus 4.8 for the 5% of genuinely hard analysis and complex agentic tool-use. Running everything on Opus is the single biggest cause of a runaway Claude bill.

Anthropic charges roughly a tenth the rate for cached reads. Cache the long, stable part of a prompt (a contract, a knowledge base, an 8K system prompt) once, then ask many questions against it. If you call 50K times a month, cached reads cut input cost by around 80%. Median configuration we hit: 90% cache rate, median saving: £10K a year.

It’s genuinely useful when you want Claude to take actions across your real systems (HubSpot, Slack, GitHub, Notion, your DB), less so for “just answer questions”. Write the tool definition once and any MCP-capable model can call it. Most production engagements we shipped in 2025 use MCP for at least one tool integration. Claude also runs on the Anthropic API, AWS Bedrock, and Google Vertex AI, so you keep your residency options.

Anthropic does not train on API data by default. We add PII redaction at the gateway, and for regulated data we run Claude via Bedrock in your VPC. Signed DPA before week one.

30-day walk-away both ways. Milestone billing 25/25/25/25. UK VAT registered, listed on Companies House, shipping since 2019.

Every Claude API integration has two senior engineers paired. Every decision into an ADR same day. Mohit reviews every PR. Two handovers in seven years, both inside 48 hours.

Yes, with 14 days’ notice. No cancellation fee.

Claude api integration — product screenshot / UI

In context

Inside the work.

A look at the kind of claude api integration surface we hand over — real screens, real data, documented and yours from day one.

Claude’s judgement, without Anthropic owning your runtime

One paragraph. That’s it.

Name the Claude capability you need, the stack, and the document or tone problem you’re solving. Mohit replies inside 24 hours: a clear yes, a clear no, or the one question that decides it.

Write to mohit@empyrealinfotech.com Replies in 24h200K context + cachingGateway + fallback

What happens after the email lands

< 24h
A personal reply.
Yes, no, or the deciding question. Straight to your inbox.
Week 1
Gateway + cost plan.
Model routing, prompt caching, fallback, eval gold set designed.
Wk 5
Shipped + portable.
Claude where it wins, swappable everywhere, cheap at scale.