LILT AI Platform
Agentic multilingual AI platform for enterprise translation and localization
- Tool type
- Agentic multilingual AI platform
- Made for
- Enterprises, public sector and AI developers
- Runs on
- Vendor platform with API and MCP integration
- Connects through pre-built connectors, API access on Enterprise plans, and MCP with any LLM; deployable in cloud, on-premise or air-gapped setups.
What it does
LILT AI Platform takes in source content such as marketing copy, product interfaces, support materials, technical documentation and regulatory text, and routes it through agentic AI translation workflows. The output is multilingual content that teams can review, approve and publish, with brand and compliance checks built into the process.
Organizations use it to consolidate translation tooling, pairing context-aware models or their own LLM with self-learning that improves from human corrections. Agents route work to human experts, either LILT's or the customer's own, and pre-built connectors let teams translate inside the business applications they already use.
It suits enterprises, public sector bodies and AI developers that need governed multilingual output. Access starts with a demo request or sales contact. Deployment can be cloud, on-premise or air-gapped, and the Government tier adds IL6+ compliance and cleared on-site support for defense and public sector work.
What it can do
- Agentic translation workflows that automate reviews and content routing
- Context-aware multilingual models, or customer-supplied LLMs, with self-learning from human feedback
- Routing of work to human subject matter experts for verification
- Governance with visibility into model use, data use and brand consistency
- Flexible deployment including private cloud, on-premise and air-gapped environments
- Forward-deployed engineers for model training and custom implementations
Works with
- Pre-built connectors to business systems
- MCP (Model Context Protocol) integration with any LLM
- API access on Enterprise plans
Example workflows
- Regulated content localization
- Input: regulatory submission or labeling text in English. Steps: agents route content through AI translation, then to expert verification for compliance. Output: multilingual content prepared for regulatory review.
- Product launch collateral
- Input: product marketing and interface strings from existing business apps. Steps: connectors pull the content, agents apply brand-aligned review, and output is returned to the same tools. Output: localized launch materials for regional teams.
Before you choose
- Pricing is not published; the pricing page directs buyers to contact sales for Business, Enterprise and Government plans.
- API access and enterprise connectors are listed under the Enterprise tier, not Business.
- Government features such as IL6+ compliance and on-site cleared support apply to Defense, Intelligence and Public Sector deployments.
Listed under
Get started
Scope needs with the sales team; pricing is handled through contact.
- Book a demo through the lilt.com homepage to scope needs with the sales team.
- Choose a plan tier (Business, Enterprise or Government) based on security and deployment requirements.
- Connect business systems using the pre-built connectors or the API/MCP integration, with forward-deployed engineers supporting custom implementation.
Plans and prices
No public prices are listed. Enterprise includes custom invoicing. MCP is available on all plans; its pricing is shown separately on the page.
- Trusted AI platform and business connectors
- Contextual AI models and agents/copilots
- Human expert verification and API access
- SSO/SAML, 99.9% uptime, managed deployment
- Cloud, cloud on-prem and air-gapped deployment
- IL6+ compliance and on-site cleared support
Source: lilt.com/pricing, checked 29 Oct 2026. Prices can change; check before you buy.
Sources for this overview
Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.
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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.