Inference infrastructure for legal tech teams
Build legal agents that find the right evidence and show their work.
SIE gives teams building legal software one API for document reading, retrieval, extraction and sensitive-text handling.
Self-host SIE in your infrastructure, or ask about managed deployment through SIE Cloud.
Which clause changes the liability cap for a data incident?
Security Addendum §3.1 overrides the general cap.
The exclusion applies to a data security incident. The base agreement cap in §8.2 does not control this claim.
The production problem
The hard part sits behind the legal agent.
Legal agents fail when source documents arrive incomplete, retrieval misses controlling text or extracted terms lose context. Fixing every step with a separate model service leaves product teams operating a fleet of serving stacks.
Evidence
The controlling clause stays buried.
Search returns a plausible provision. The amendment, exception or later version ranks below it.
Documents
Structure gets lost before analysis starts.
Scans, exhibits, signature pages and tables arrive as broken text. The agent begins with an incomplete record.
Extraction
Fields look right until review finds the error.
An effective date becomes a notice deadline. A condition disappears from the extracted obligation.
Data control
Sensitive files block the path to production.
Matter data may require approved providers, regional processing, tenant isolation or deployment inside your cloud.
How SIE fits
One inference layer for the model work behind your legal product.
Your team builds the legal workflow and user experience. SIE runs document parsing, OCR, embeddings, rerankers, extraction and guardrails through one API. Add tasks without deploying and operating another model server.
Read the source files.
Convert PDFs, Office files, scans and page images into clean text while preserving tables, headings and reading order.
Measured tradeoffs
Price, quality and latency for the work behind a legal agent.
Each view compares models on the same task. Switch workloads to see the measured cost and quality tradeoffs, with latency where this pair was timed.
Rerank legal and regulatory evidence.
499 Federal Register questions with 20 candidates each, under two relevance rules. A question is right when the requested document ranks first under both rules.
Rerank 3x faster than Cohere Rerank 4 Pro, 94% cheaper
Each model at its list price; SIE at its Serverless price. SIE timed on a GPU server with the client alongside; providers over their public APIs. The task comparison includes the other measured models and settings.
View task comparison dataA useful first test
Test the failure you already see in review.
Choose one workflow, one approved document set, one current baseline and one acceptance threshold. A narrow test produces a clear decision.
Get startedEvidence retrieval
Rerank labeled passages from contracts, court records, regulations or patents.
Document reading
Run OCR or document-to-Markdown on the formats that create the most correction work.
Term extraction
Extract renewal terms, notice periods, obligations or matter events into your schema.
Sensitive-text handling
Detect and mask the entity types covered by your data policy.
Recorded example
Contract review with source-cited findings.
Model stages collect and test the contract evidence
Deployment
Run SIE where your legal data can go
Start locally, self-host in your own infrastructure, or talk to us about managed deployment through SIE Cloud. The legal tasks on this page run through one inference engine, without a separate serving stack for every model or workflow.
Use SIE Cloud
Managed deployment for teams that do not want to build and operate a separate model-serving stack.
- Serverless usage
- US or EU data residency
- SOC 2 Type 2 controls
- No idle GPU capacity to fund
Run SIE in your infrastructure
Self-host where document security, data residency or customer requirements demand it.
- Terraform deployment for major clouds
- Tenant-specific worker pools
- Scale-to-zero support
- Apache 2.0 source
Need a laptop check before production? Run locally with the quickstart
Need to confirm retention, subprocessors, regional processing or tenant isolation? Review those requirements before moving private matter data.
Run every legal-agent model through one serving stack.
SIE Cloud or self-hosted
Choose the right setup for your legal workflow.
SIE Cloud gives legal tech teams managed inference. The same open-source engine runs in your own infrastructure when your data policy requires it. Talk to the people who build SIE about workload volume, data boundaries and deployment.
Pilot brief
What to bring to the conversation
We will use these details to map the workflow, compare SIE Cloud with self-hosting and define a test your team can judge.