step 01
Ground in your help center
qwen3-embedding Retrieve from your knowledge base, docs and past tickets so answers are accurate and on-policy, grounded in your reality, not a generic model's.
// use cases · customer support
Deflect and answer tickets and conversations across chat, email and voice, grounded in your help center, with customer data that never leaves the EU.
// how it works
Retrieval, reasoning, tools and voice from a single OpenAI-compatible endpoint, across every channel, and only inside the EU.
step 01
qwen3-embedding Retrieve from your knowledge base, docs and past tickets so answers are accurate and on-policy, grounded in your reality, not a generic model's.
step 02
deepseek-v4-flash Resolve tickets and chats with tool calling, look up orders, check accounts, take actions, and escalate cleanly to a human when it's the right call.
step 03
kokoro Chat, email or voice, transcribe and speak with whisper-large-v3 and kokoro for voicebots and IVR. One stack, every customer touchpoint.
// drop-in
Grounded answers with tools, one chat completion. Change the base URL and key and your support bot runs on private EU models.
read_the_docsfrom openai import OpenAI client = OpenAI( api_key="sk-...", base_url="https://api.helmcode.com/v1", # one line changes ) # answer from your help center, with tools to take action reply = client.chat.completions.create( model="deepseek-v4-flash", messages=[ {"role": "system", "content": "Answer from the help center." + kb_context}, *conversation, ], tools=tools, # look up orders, check accounts )
// why helmcode
Every ticket and call is full of customer PII. Closed APIs want all of it, the messages, and the recordings.
Tickets, chats and recordings are never logged, and never train a model. The personal data in a conversation stays exactly where it should.
Conversations and customer data stay on EU infrastructure, not on US hyperscalers subject to the Cloud Act. GDPR and AI Act native.
Every ticket, message and minute is included. Limits are RPM and concurrency per key, never total tokens, so cost per interaction drops as volume grows.
Text and voice, STT, LLM and TTS, behind a single OpenAI-compatible endpoint. One stack for tickets, chat and voicebots.
Answers retrieved from your own knowledge base, with citations, fewer hallucinations, fewer wrong answers, fewer escalations.
OpenAI-compatible chat, tools and audio. Change the base URL and key; your helpdesk, CCaaS or bot framework keeps working.
// support faq
What CX and engineering teams ask before automating support on their own data.
Yes. Ground answers with retrieval (qwen3-embedding + rerank) over your knowledge base, docs and past tickets, so responses are accurate and on-policy, with citations.
Yes. With tool calling it can look up orders, check accounts and trigger workflows, then escalate to a human when needed, the same JSON tools you already use with OpenAI.
Yes. Transcribe calls with whisper-large-v3 and synthesize replies with kokoro (sub-second, 67 voices) for voicebots and IVR, all from the same API.
No. Zero logs, conversations, transcripts and recordings are never persisted and never train a model.
Flat-rate pricing with no token caps means every deflected ticket and message is included, so as volume grows, your cost per interaction falls instead of rising.
Yes. Run on a dedicated GPU or fully on-premise inside your own datacenter, the same API and code, with customer data that never leaves your network.
// get started
Skip the AI infra work. Deploy your first private inference endpoint today.
Flat rate. EU data. OpenAI API compatible.
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