Run document processing, data enrichment, and other batch AI workloads through an OpenAI-compatible API. Work queues to GPUs that would otherwise sit idle, so you pay for completed compute — not reserved capacity, not idle time.
Point your base_url at MicroDC.ai and keep the OpenAI client you already have.
Stream the response or let it complete in the background. End-to-end encrypted
payloads available for sensitive workloads.
# pip install openai from openai import OpenAI client = OpenAI( base_url="https://api.microdc.ai/v1", api_key=os.environ["MDC_KEY"], # mDC_... ) resp = client.chat.completions.create( model="llama3.3:70b", messages=[{"role": "user", "content": "..."}], ) print(resp.choices[0].message.content)
curl https://api.microdc.ai/v1/chat/completions \
-H "Authorization: Bearer $MDC_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "llama3.3:70b",
"messages": [{"role":"user","content":"..."}]
}'
# OpenAI-shaped response. Add "stream": true for SSE.
# Batch work? POST /api/v1/jobs — see the API reference.
REST, Python, OpenAI-compat. Submit jobs, get results. Encrypted payloads for sensitive workloads. Custom-amount credits — no minimums, no monthly fees.
Shared team budgets, per-member spend caps, and private worker groups your jobs route to exclusively. Start on a credit card, move to an invoice when it matters.
Connect a worker in five minutes. Context-tier routing means low-spec hardware still earns. Multi-GPU and concurrent jobs supported. Payouts in credits or PayPal.
POST your job — model, payload, and optional encryption keys. You get a job id back immediately.
Our scheduler matches the job to a worker tier with the right VRAM, locality, and price ceiling.
A worker pulls, runs, and returns. Streaming token deltas where applicable.
Poll the job id, or let the SDK wait for you. Every job lands in your billing ledger with its own line item.
Summarize tens of thousands of PDFs, extract structure from contracts, normalize OCR output. Queue at 2am, deliver at 6am.
Run grids of experiments across model × prompt × dataset. No reservation, no spin-up time, no idle burn.
Classify, tag, embed, and score records at warehouse scale. Pull results back into your ETL on your own schedule.
Personalized summaries, briefs, and translations. Rate-limit-free batches.
Plug LLM steps into Airflow, Temporal, or n8n. Automatic retries, per-job cost on every line.
Submit during business hours, results on your morning desk. Cheapest tier.
No credit card to start. No monthly minimum. Free credits for evaluation, and a real person on the other end when you are sizing something larger.