Stage 01
Intelligent Ingestion
High-fidelity OCR and structural layout analysis extract headings, tabular data, diagrams, and footnotes with semantic hierarchy intact.
An NVTS Product
NV Vector
High-Dimensional Enterprise Document Vectorization & Semantic Retrieval
Stop losing critical institutional knowledge in dead PDFs and legacy archives. NV Vector parses, embeds, and indexes enterprise documentation with pinpoint accuracy and source-cited verification.
Vectorization Architecture
The NV Vector Ingestion Pipeline
Traditional search looks for exact words. NV Vector models the conceptual relationships inside your technical documentation.
Stage 02
Contextual Chunking
Dynamic token windowing ensures clauses, tables, and mathematical formulas are never chopped mid-thought, preserving full semantic context.
Stage 03
Dense Embeddings
Domain-adapted embedding models generate high-dimensional vectors capturing nuanced industry terminology and synonyms.
Stage 04
Cited Retrieval API
Hybrid sparse-dense retrieval surfaces top answers in sub-50ms with cryptographically verifiable page and bounding-box coordinates.
Capabilities
Engineered for High-Stakes Accuracy
Designed for organizations where hallucinations are unacceptable: engineering firms, legal departments, medical compliance, and financial auditors.
Strict Zero-Hallucination Guardrails
NV Vector forces downstream LLMs to cite retrieved chunks verbatim. If evidence does not exist in the source index, the system declares absence rather than inventing facts.
Private Tenant Deployment
Runs entirely inside your Azure, AWS, or local cluster. Your intellectual property and sensitive customer records are never used to train external models.
Enterprise API Ready
REST and gRPC endpoints let you plug NV Vector directly into Slack bots, internal web portals, Teams copilots, and core operational software.
Powered by NVTS
Bring Vector Search to Your Document Library
Let us benchmark NV Vector against your most complex technical manuals or contract archives.