On-prem SLM inference vs rented GPU cloud: how to choose
The decision is not ideological—it is a bundle of networking, procurement, incident response, and unit economics that changes with your traffic shape.
Continue reading →Industries
Who it's for
Industry patterns we design for. Each card links to a focused use-case overview.
- Financial ServicesAML screening, fraud signals, and contract clauses - on your infrastructure.View use case →
- LegalHigh-volume review, extraction, and diligence without data leaving your boundary.View use case →
- Professional ServicesAutomate repetitive office work: documents, email, reporting, and data entry.View use case →
- ManufacturingQuality reports and maintenance signals at the edge - with predictable latency.View use case →
- Government & DefenseAir-gapped and classified patterns where public APIs are not an option.View use case →
Our models
SLM-Works Models
Task-specific SLMs we built and fine-tuned for real business workflows. Run on your infrastructure, save up to 96% on tokens, and keep your data private.
Available
SLM-Works Invoice Generator
Structured invoice creation from unstructured input
Fine-tuned to extract line items, tax calculations, payment terms, and vendor details from emails, PDFs, and chat messages - then output clean, structured invoice data ready for your ERP or accounting system.
3B~92% fewer tokens per invoice vs GPT-4
- Extract line items from unstructured text, email, or scanned PDFs
- Multi-currency support with automatic tax calculation logic
- Output structured JSON matching common ERP schemas
Available
SLM-Works Contract Analyzer
Clause extraction and risk flagging for legal documents
Purpose-built to read contracts, extract key clauses (liability, termination, IP, SLA), flag deviations from your standard templates, and surface risk areas - without sending confidential documents to external APIs.
3.8B~88% fewer tokens per contract review vs GPT-4
- Extract and classify 20+ standard contract clause types
- Flag deviations from your baseline templates
- Risk scoring per clause with plain-language explanations
Available
SLM-Works Support Classifier
Instant ticket routing and intent detection
Trained on enterprise support patterns to classify incoming tickets by category, urgency, sentiment, and required skill group - enabling instant routing and SLA-aware prioritization without manual triage.
1B~96% fewer tokens per classification vs GPT-4
- Classify tickets across 50+ configurable categories
- Detect urgency level and customer sentiment in one pass
- Sub-10ms inference latency for real-time routing
Available
SLM-Works Doc Summarizer
Concise summaries of long-form business documents
Fine-tuned for enterprise document types. board reports, policy documents, technical specs, RFPs. to produce accurate, structured summaries with key decisions, action items, and risk callouts highlighted.
2B~90% fewer tokens per summary vs GPT-4
- Summarize documents up to 32K tokens in a single pass
- Extract key decisions, action items, and deadlines
- Configurable output: executive brief, bullet points, or structured JSON
Coming soon
SLM-Works Data Extractor
Structured data from messy sources
Purpose-built to pull structured data from emails, forms, reports, and semi-structured documents. names, dates, amounts, reference numbers. and output clean, validated records for downstream systems.
3B~91% fewer tokens per extraction vs GPT-4
- Entity extraction across 30+ field types (dates, amounts, names, IDs)
- Handle multi-language input with consistent output schema
- Built-in validation and confidence scoring per field
Coming soon
SLM-Works Code Reviewer
Automated code review for common enterprise stacks
Fine-tuned on enterprise code review patterns to flag security issues, style violations, performance bottlenecks, and logic errors. runs entirely in your CI/CD pipeline without external API dependencies.
6.7B~85% fewer tokens per review vs GPT-4
- Security vulnerability detection (OWASP Top 10 patterns)
- Style and convention checks for Java, Python, TypeScript, Go
- Performance anti-pattern flagging
Available
SLM-Works Email Drafter
Professional emails from bullet points or voice notes
Fine-tuned to transform brief instructions, bullet points, or raw voice transcripts into well-structured, on-brand professional emails. Adapts tone and formality to recipient context and produces send-ready drafts in seconds.
2B~91% fewer tokens per draft vs GPT-4
- Draft complete emails from 3–5 bullet points or a raw voice note
- Tone adaptation: formal, consultative, assertive, or friendly
- Context-aware subject line and opening line generation
Available
SLM-Works HR Screener
CV screening and candidate data extraction at scale
Purpose-built to parse CVs and cover letters, extract structured candidate profiles, and score applicants against job requirements you define. Reduces first-pass review time from hours to seconds without sending sensitive data outside your network.
1B~95% fewer tokens per CV vs GPT-4
- Extract 25+ structured fields: skills, tenure, education, certifications
- Score candidates against weighted criteria from your job description
- Flag missing requirements and experience gaps with plain explanations
Available
SLM-Works Feedback Analyzer
Structured insight from customer feedback and NPS responses
Classifies and extracts themes, sentiment, urgency, and product signals from free-text survey responses, NPS comments, support reviews, and social feedback. Turns unstructured voice-of-customer data into consistent, queryable output.
2B~92% fewer tokens per response vs GPT-4
- Multi-label sentiment and topic classification in one pass
- Extract product mentions, feature requests, and churn signals
- Urgency and escalation scoring for negative feedback
Coming soon
SLM-Works Meeting Scribe
Transcripts to structured minutes and action items
Converts raw meeting transcripts into formatted minutes with agenda sections, key decisions, action items with owners, and deadlines. Works with transcripts from any video conferencing tool and adapts to your minute template.
3B~89% fewer tokens per meeting vs GPT-4
- Detect and extract action items with assigned owner and deadline
- Segment transcript by agenda topic automatically
- Configurable output: executive summary, full minutes, or action list only
Coming soon
SLM-Works RFP Analyzer
Tender and RFP parsing for faster bid decisions
Parses RFPs, tenders, and procurement documents to extract requirements, evaluation criteria, mandatory qualifications, deadlines, and scoring weights. Surfaces bid/no-bid signals so your team focuses effort on winnable opportunities.
3.8B~87% fewer tokens per RFP vs GPT-4
- Extract mandatory and scored requirements with page references
- Identify evaluation criteria and their weighting from tender documents
- Flag compliance risks, missing prerequisites, and tight deadlines
Coming soon
SLM-Works Compliance Checker
Policy conformance screening for outgoing content
Screens outgoing communications, contracts, marketing content, and internal documents against your defined policy rules. Flags violations, suggests compliant rewrites, and logs every check for audit purposes - entirely on your infrastructure.
3B~90% fewer tokens per check vs GPT-4
- Check content against 100+ configurable policy rules simultaneously
- Violation explanation with specific clause reference and severity
- Suggest minimal compliant rewrites preserving original intent
Need a custom SLM for a different task?We build those too →
How it works
The SLM pipeline in four steps
From governed data to production inference: how we take you from experiment to owned, efficient models.
Overview
Explore the four-step pipeline
Select a pipeline stage to read a short summary. Four steps from data through deployment.
Data engineering & curation
Shape domain corpora, labels, and governance so small models learn what matters.
Learn more: Custom SLMMore detail
We help you curate PDFs, structured data, and internal knowledge bases with clear ownership, eval sets, and safety boundaries before training begins.
Model compression
Distillation, quantization, and pruning to cut latency, cost, and footprint.
Learn more: Custom SLMMore detail
Teacher–student distillation plus aggressive quantization and pruning where appropriate so production inference stays fast on your hardware budget.
PEFT / LoRA fine-tuning
Adapt behavior with parameter-efficient updates instead of full retraining.
Learn more: Custom SLMMore detail
LoRA and related PEFT methods align the compressed model with your jargon, policies, and task formats without blowing up training cost.
Deployment & orchestration
Ship to on-prem, VPC, or rented GPU footprints with runbooks and monitoring.
Learn more: SLM infrastructureMore detail
We operationalize inference runtimes, sizing, observability, and handover - paired with SLM infrastructure options when you need us to run the stack.
By the numbers
Enterprise performance, proven
96%Token savingsvs cloud LLM APIs like GPT-4
1B–70BParameter rangeRight-sized for every use case
< 10msInference latencyOn compact SLM deployments
ZeroData egressEverything runs in your boundary
Deploy on any major cloud or on-premise
Ready to move from AI experiment to AI production?
Start with a scoped proof of concept or a short discovery call, and we keep the conversation focused on SLM delivery and your infrastructure.
Evaluating SLMs internally? Download the Enterprise SLM Buyer's Guide (PDF).