Background Image

Private AI that never

leaves the building

Build and run language models fully inside your infrastructure. Your data, your model, your control.

Background Image

Private AI that never

leaves the building

Build and run language models fully inside your infrastructure. Your data, your model, your control.

Background Image

Private AI that never leaves the building

Build and run language models fully inside your infrastructure. Your data, your model, your control.

Own your intelligence. Don't rent it

Build AI that belongs to you, trained on your data and running on your terms.

Private Efficient No API Costs Runs Anywhere Compliance Ready

Own your intelligence. Don't rent it

Build AI that belongs to you, trained on your data and running on your terms.

Private Efficient No API Costs Runs Anywhere Compliance Ready

PROBLEM

Engineering teams need efficient, private, and low-cost AI they truly own.
Engineering teams need efficient, private, and low-cost AI they truly own.
Engineering teams need efficient, private, and low-cost AI they truly own.
Engineering teams need efficient, private, and low-cost AI they truly own.
OpenSLM’s low-code platform turns company data into small language models running fully on your own infrastructure — no data risk, no API bills.
OpenSLM’s low-code platform turns company data into small language models running fully on your own infrastructure — no data risk, no API bills.
OpenSLM’s low-code platform turns company data into small language models running fully on your own infrastructure — no data risk, no API bills.
OpenSLM’s low-code platform turns company data into small language models running fully on your own infrastructure — no data risk, no API bills.

PERFORMANCE

One platform to build, train, run, test your own language models

OpenSLM is a low-code platform that helps engineering teams turn company data into small language models that run fully on their own infrastructure. No big ML team. No data risk. No API bills.

Build without the heavy lifting

Guided tools handle data preparation, model selection, and fine-tuning, so your team can focus on results.

Build without the heavy lifting

Guided tools handle data preparation, model selection, and fine-tuning, so your team can focus on results.

Full control when you want it

Engineers can change training settings, model setup, and deployment details with complete code access.

Full control when you want it

Engineers can change training settings, model setup, and deployment details with complete code access.

Deploy with one SDK

Connect your model to any app, server, or device using a simple SDK and API.

Deploy with one SDK

Connect your model to any app, server, or device using a simple SDK and API.

Industry Use Cases

The next step for AI: efficient, private, and low-cost.

Most companies use AI that is costly, slow to control, and runs outside their walls. Better operations need a better kind of AI.

E-commerce & Logistics

Use it for

Customer support, order tracking questions, return handling, and delivery updates.

Also for operations

Reading invoices, sorting shipment data, and route or warehouse queries.

Result

Save up to 60%+ on yearly AI costs while handling thousands of daily customer chats in-house.

Healthcare

Use it for

Summarizing patient records, answering staff questions from medical guidelines, and processing insurance claims.

Also for operations

Local EHR analysis, triage support, and clinical coding with strict medical confidentiality.

Result

Keep patient data fully private and easier to manage under health data rules, while saving up to 50–60% on AI costs.

Fintech & Banking

Use it for

Fraud alert explanations, KYC document checks, loan document review, and customer support.

Also for operations

Transaction auditing, credit risk assessment synthesis, and anti-money laundering telemetry.

Result

Sensitive financial data never leaves your system, with up to 60% lower AI running costs.

Oil & Gas

Use it for

Searching safety manuals, maintenance reports, and equipment logs.

Also for operations

Works onsite, even without internet, on rigs and remote industrial locations.

Result

Instant answers for field teams in remote sites, with no cloud dependency and up to 55%+ savings.

Manufacturing

Use it for

Quality reports, machine maintenance guides, and shift handover summaries on the factory floor.

Also for operations

Real-time edge analysis directly on factory PCs and embedded IoT line controllers.

Result

Faster decisions on the floor, with AI that runs on local devices and costs up to 50%+ less.

Legal & Insurance

Use it for

Contract review, claim document processing, and searching past case files.

Also for operations

Privileged discovery search, policy comparison, and regulatory compliance validation.

Result

Confidential documents stay in-house, with up to 60% lower AI costs on high-volume review work.

Cross-Sector Adoption

Different industries. Same need: fast, private, low-cost AI.

From high-frequency finance to offline field operations, small language models power mission-critical tasks everywhere.

E-commerce Logistics Healthcare Fintech Banking Insurance Oil & Gas Manufacturing Legal Telecom E-commerce Logistics Healthcare Fintech Banking Insurance Oil & Gas Manufacturing Legal Telecom
Energy & Utilities Government Education Retail Hospitality Travel & Aviation Automotive Pharma Construction Agriculture Energy & Utilities Government Education Retail Hospitality Travel & Aviation Automotive Pharma Construction Agriculture

PROVEN METRICS & UNIT ECONOMICS

Proven efficiency, guaranteed privacy, and radical cost reduction across your infrastructure.

60%+

Cost Reduction

Save up to 60%+ on annual model compute and API bills by switching to task-specific small models.

<50ms

Local Latency

Zero network hops. Models run directly on your infrastructure for instantaneous edge and server responses.

100%

Data Sovereignty

Full air-gap compatibility. Your training corpora and prompts never leave your private perimeter.

FAQ

Frequently Asked Questions

Get answers to common questions here

How does OpenSLM ensure data never leaves our building?

All model training, fine-tuning, and inference run entirely within your own virtual private cloud (VPC), on-premises servers, or edge hardware. No training data, prompts, or weights are ever transmitted to external third-party servers.

What hardware is required to run Small Language Models?

Unlike massive 70B+ LLMs that require expensive multi-GPU clusters, OpenSLM specializes in highly optimized small language models (1B to 8B parameters) that run on standard CPUs, single enterprise GPUs, Apple Silicon, or embedded edge devices.

Can we fine-tune models on custom internal enterprise data?

Yes. OpenSLM includes built-in automated pipelines for data extraction, deduplication, synthetic dataset generation, LoRA/QLoRA fine-tuning, and direct domain adaptation from PDFs, relational databases, internal wikis, and customer support tickets.

How does OpenSLM compare to hosted cloud LLM APIs (OpenAI, Anthropic)?

For specific enterprise tasks (support routing, invoice parsing, medical triage, contract reviews), task-specific small models match or beat generalist models in accuracy, while delivering 5x lower latency, 60%+ lower cost, and complete data privacy.

Do our developers need extensive machine learning or data science expertise?

Not at all. OpenSLM is built as a developer-friendly low-code platform with guided workflows, pre-configured recipes, and a single-line SDK for Python, Node.js, C++, and REST/gRPC endpoints.

How does OpenSLM ensure data never leaves our building?

All model training, fine-tuning, and inference run entirely within your own virtual private cloud (VPC), on-premises servers, or edge hardware. No training data, prompts, or weights are ever transmitted to external third-party servers.

What hardware is required to run Small Language Models?

Unlike massive 70B+ LLMs that require expensive multi-GPU clusters, OpenSLM specializes in highly optimized small language models (1B to 8B parameters) that run on standard CPUs, single enterprise GPUs, Apple Silicon, or embedded edge devices.

Can we fine-tune models on custom internal enterprise data?

Yes. OpenSLM includes built-in automated pipelines for data extraction, deduplication, synthetic dataset generation, LoRA/QLoRA fine-tuning, and direct domain adaptation from PDFs, relational databases, internal wikis, and customer support tickets.

How does OpenSLM compare to hosted cloud LLM APIs (OpenAI, Anthropic)?

For specific enterprise tasks (support routing, invoice parsing, medical triage, contract reviews), task-specific small models match or beat generalist models in accuracy, while delivering 5x lower latency, 60%+ lower cost, and complete data privacy.

Do our developers need extensive machine learning or data science expertise?

Not at all. OpenSLM is built as a developer-friendly low-code platform with guided workflows, pre-configured recipes, and a single-line SDK for Python, Node.js, C++, and REST/gRPC endpoints.

Efficient. Private. On-device AI.

Your data, your model, your control.

Efficient. Private. On-device AI.

Your data, your model, your control.

Efficient. Private. On-device AI.

Your data, your model, your control.