NebulaForge provides secure, high‑throughput pipelines for LLM training, fine‑tuning, and inference data. Store, version, and serve billions of tokens with enterprise‑grade privacy and SLAs.
curl -X POST https://api.nebulaforge.ai/v1/ingest \ -H "Authorization: Bearer $NEBULA_TOKEN" \ -F "dataset=@/path/to/corpus.parquet" \ -F "deduplicate=true" \ -F "hash_col=id" \ -F "lang=en"
From raw data to serving billions of embeddings, NebulaForge unifies storage, processing, and delivery for LLM workloads.
Schema-aware ingestion with on‑the‑fly language detection, PII redaction, canonicalization, and exact/近似 deduplication.
Multi‑tenant vector DB with HNSW/IVF, hybrid keyword + semantic search, and streaming updates for agentic RAG.
Immutable snapshots, bucket versioning, lifecycle policies, and geo‑replication for training corpora and checkpoints.
Sharded, fault‑tolerant workers with backpressure and retries. 20 GB/s per rack sustained.
SOC 2 Type II, ISO 27001, GDPR DPA. Region pinning and per‑tenant KMS keys.
Multi‑CDN with signed URLs and smart cache keys to accelerate fine‑tuning and inference I/O.
Per‑pipeline metrics, token‑aware cost tracing, and data lineage for governance.
Rule‑guided generation with safety filters and eval‑ready feedback loops.
Active learning, clustering, dedup, and domain filters. Export to DPO formats.
Private networking, per‑dataset ACLs, field‑level encryption, and tamper‑evident logs.