API
REST and webhook endpoints with OpenAI-compatible schemas, SDK examples and a sandbox tenant for testing.
AI solutions
Language and generation infrastructure you can build a business on
Three tightly coupled layers — translate, create and token — exposed as APIs, dashboards and white-label products. Use one, or run them together as a single localisation pipeline.
Layer 01 — Translate
Translation that respects your vocabulary
Volume alone is not quality. We combine neural engines with domain glossaries, translation memory and optional human review, so product documentation, marketing copy and support conversations read as if one person wrote them — in every language.
- Documents, subtitles, UI strings, chat and live speech
- Glossary enforcement and translation-memory reuse
- Human-in-the-loop review with quality scoring
- 30+ locales including RTL typography and formatting
Layer 02 — Create
From brief to finished assets, repeatably
We turn generation models into production lines. Prompt templates are versioned like code, jobs are queued and retried, and every asset carries its provenance — so brand, legal and local teams can all trust what ships.
- Copywriting, image, voice-over and short-video pipelines
- Versioned prompt libraries with A/B evaluation
- Batch orchestration, retries, queues and rate governance
- Provenance records, licensing notes and moderation gates
Layer 03 — Token
One gateway in front of every model
Provision keys per team or per customer, set budgets, cache repeat requests, fail over between providers and attribute spend down to the individual request — without rewriting the application that consumes them.
- Bring your own keys or draw from a managed pool
- Routing, retries, failover and semantic caching
- Per-project budgets, quotas and anomaly alerts
- OpenAI-compatible endpoints and white-label resale ready
How it fits together
One pipeline instead of three vendors
Because all three layers share the same gateway, glossary and observability stack, an asset can move from brief to twelve localised variants without manual handoffs.
Ingest
Connect documents, product copy, tickets or a DAM/CMS source through API, webhook or connector.
Generate
Versioned prompt templates produce copy, images, voice or video with provenance attached.
Translate
Neural engines apply your glossary and memory; flagged segments go to human review.
Review
Brand, legal and local reviewers approve in one queue with full revision history.
Publish
Approved assets return to your CMS, store listing or CDN — metered through the token gateway.
Delivery options
Consume the layers however suits your team
Managed dashboard
A hosted console for non-technical teams: submit jobs, follow review queues and export results.
White label
Rebrand the whole stack, set your own pricing and margins, and resell AI capacity to your customers.
Typical use cases
Where teams start
Product localisation
Ship documentation, UI strings, release notes and in-app help in many languages at once, keeping one glossary across all of them.
Campaign production
Generate hundreds of on-brand variants per campaign, localise captions and subtitles automatically, then route everything through one approval queue.
Reselling AI capacity
Use the token gateway to package models into your own plans — metered, budgeted and invoiced under your brand.
FAQ
Solutions questions
Neural translation handles high-volume content well, especially when paired with a domain glossary and translation memory. For customer-facing or regulated material we add human review so terminology stays consistent and quality can be scored before publication.
More than 30 locales are supported, including Chinese, Japanese, Korean, Spanish, French, German, Portuguese, Arabic and Hebrew. Right-to-left layouts and locale-aware formatting are part of the default integration work.
Every request runs through a token gateway with per-project budgets, semantic caching, retries and automated failover between providers. Usage dashboards attribute spend down to individual features, and budget alerts fire long before a limit is reached.
Yes. You can bring your own keys, draw from a managed pool, or route sensitive workloads to a private or self-hosted deployment. The API surface stays identical, so nothing in your application changes.
Integration normally happens through REST endpoints or webhooks, plus connectors for common CMS, helpdesk and repository systems. We ship SDKs, request examples and a sandbox tenant so your team can test before anything reaches production.
You do. Input content, prompts and generated assets belong to you, are processed only to deliver the requested service, and are never used to train models.
See these layers running against your own content.
Send us a sample document or brief and we will return a localised, generated sample with realistic latency and cost figures.