Enterprise Document Intelligence, Engineered to Scale
Turn millions of documents into answers your teams can act on.
StreamIndexAI is the unified AI-powered distributed data platform for enterprise knowledge — ingestion, indexing, and retrieval at production scale, with the sharding, queueing, and performance engineering already built in.
14-day free trial. No distributed-systems team required.
documents indexed in live pipelines
p95 query latency at 10M+ doc scale
ingestion pipeline uptime
Every piece of distributed-systems engineering, already solved.
Stop assembling queueing, sharding, and retrieval infrastructure from disparate tools. StreamIndexAI ships it as one opinionated, enterprise-ready platform.
Elastic Ingestion Pipelines
Auto-scaling worker pools ingest and normalize any format — PDFs, DOCX, emails, scanned archives — without your team hand-tuning sharding or backpressure.
Distributed Search & Retrieval
Sub-second hybrid search (vector + lexical) across tens of millions of documents, load-balanced and query-planned automatically as your corpus grows.
AI-Native Structured Extraction
LLM-powered extraction pulls entities, clauses, and obligations out of unstructured documents, tuned per document type with no prompt engineering required.
Built-In Fault Tolerance
Queueing, retries, and dead-letter handling are part of the platform, not something your engineers bolt on after the first silent data-loss incident.
One Knowledge Layer, Every Silo
SharePoint, S3, email archives, and scanned records become a single queryable index — no more stitching together five search tools by hand.
Enterprise Security & Governance
Role-based access, full audit trails, and data-residency controls are enforced at the platform level, ready for your compliance review on day one.
Trusted by teams who used to own this problem themselves.
“We had a team of platform engineers whose entire job was keeping our document pipeline from falling over under load. StreamIndexAI replaced that effort in a single quarter.”
“Search latency across our 40-million-document contract archive dropped from minutes to under a second, and we didn't touch our infrastructure team's roadmap to get there.”
“Finally an index that doesn't buckle when legal dumps another two million filings into the pipeline overnight.”
Simple pricing. Enterprise-grade platform.
Every plan includes a 14-day free trial — no distributed-systems team, no multi-quarter build-out.
Starter
For teams standing up their first enterprise-scale document pipeline.
- ✓Up to 2M documents indexed
- ✓S3, SharePoint, and database connectors
- ✓Fast, ranked full-text search across your corpus
- ✓Standard support (business hours)
Pro
For teams running document intelligence at real production scale.
- ✓Up to 25M documents indexed
- ✓All connectors, including custom database sources
- ✓Role-based access, audit trails, and retention policies
- ✓No-code pipelines for filtering, redaction, and access rules
- ✓Priority support & onboarding engineer
Indexing more than 25M documents? Contact sales for custom enterprise scale.
Questions from teams who've been burned by "just use Elasticsearch."
How is this different from building on Elasticsearch or OpenSearch ourselves?+
Those are components, not a platform. StreamIndexAI ships the opinionated distributed layer on top — sharding, queueing, autoscaling workers, and hybrid retrieval — that most teams spend a year of engineering time assembling around a raw search engine. You get the outcome without owning the infrastructure toil.
Can it actually handle our existing scale — tens of millions of documents?+
Yes. The ingestion and indexing layers are built on horizontally-scaled worker pools and sharded indices from the ground up, not retrofitted for scale later. Pilot deployments run in the hundreds of millions of documents today.
What about data security and compliance?+
Role-based access control, full audit logging, encryption at rest and in transit, and configurable data-residency are built into the platform, not offered as a paid add-on. Our team supports enterprise security review as part of onboarding.
Do we need to migrate off our existing document stores?+
No. StreamIndexAI connects to your existing repositories — SharePoint, S3, email, scanned archives — and ingests in place. There's no forced migration off systems your teams already depend on.
What does onboarding actually look like?+
Most pilots are indexing real production documents within the first two weeks, not the two-quarter timeline typical of a custom-built pipeline. Your success team scopes connectors and extraction schemas with you up front.
Does this replace our engineering team?+
No — it removes the distributed-systems toil (sharding, queue management, index rebalancing) so your engineers can focus on the products built on top of the data, instead of keeping the pipeline alive.