LILT
LILT: LILT combines adaptive AI, human review, terminology controls, and enterprise workflows. Ranked #11 of 24 in AI Translation Tools by our editors (8.3/10); pricing: Pricing on request; best for enterprise teams combining AI and human review.
At a glance
- Editor score8.3 / 10
- PricingPricing on request
- Best forEnterprise teams combining AI and human review
- Free planNo
- Founded2015
- Facts checked22 Sep 2026
Where it wins
- Adaptive AI models learn from translation feedback
- Human verification, QA, termbases, and translation memory
- Connectors, REST APIs, and private deployment options
Where it doesn't
- Pricing requires a contact-sales process
- The listed platform coverage is web only
- API access and expert verification are Enterprise features
Our verdict on LILT
LILT is a multilingual content and translation platform for commercial organizations, governments, translators, and localization teams. It combines AI and human-in-the-loop translation with document workflows, translation memory, matching, terminology management, quality assurance checks, and workflow automation. Its focus is enterprise localization: teams can create and translate content with contextual AI models, then add human expert verification where the workflow requires it. LILT also supports connections to business and content systems, external translation engines, and platform services through a REST API.
The plan structure separates capabilities by organizational need. Business includes business connectors, contextual AI models, and agents and copilots. Enterprise adds API access, human expert verification, enterprise connectors, plus SSO/SAML and managed deployment. Government includes cloud, on-premises, and air-gapped deployment, IL6+ compliance support, and cleared support. Each listed plan uses contact-sales pricing, so LILT is positioned for teams evaluating deployment, access, and review requirements rather than choosing from a self-serve pricing table. Buyers should map their workflow to the plan distinctions before selecting an edition.
LILT’s strongest fit is an organization that needs more than machine translation alone. Translation memory and termbases support consistency, while contextual models can adapt from translation feedback. Connectors cover Amazon, Google, DeepL, OpenAI, and more than 100 business systems, giving teams options for incorporating existing tools. Enterprise API access supports custom translation and platform services, while Government deployment choices address controlled environments. Teams seeking a lightweight, platform-flexible translation tool or a simple self-serve purchase may prefer an alternative; LILT is better suited to enterprise teams that value governed workflows, human review, and deployment controls.
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LILT pricing
LILT fact sheet
| Free plan | No |
|---|---|
| Paid from | Not verified |
| Languages supported | Not verified |
| Document translation | Yes |
| API access | Yes |
| Glossary support | Yes |
| Translation memory | Yes |
| Browser extension | Not verified |
| Available platforms | Web |
| Deployment | Cloud, Self-hosted |
| Platforms | Web |
| Compliance & security | SOC 2, GDPR, HIPAA, SSO/SAML, 2FA |
| Support | Docs · 24/7 |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Integrations | 100+ integrations: Content systems, Business systems, LLMs, MCP, REST API See all → |
| Pricing | Pricing on request (source) |
| Website | lilt.com |
| Facts checked | 22 Sep 2026 |
LILT integrations
LILT lists 100+ integrations on its own site — the 5 named here are the ones its pages call out.
- Content systems
- Business systems
- LLMs
- MCP
- REST API
Alternatives to LILT
- DeepL TranslatorA broad AI translation service with free access, APIs, glossaries, and translation memory.9.4
- Google TranslateA free, broad translation service for everyday use across web and mobile.9.2
- Google Cloud TranslationA deep Google Cloud translation service for teams building multilingual workflows.9.1
Also Ranked In
LILT is ranked in 5 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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