Serve Hebrew and English customers from a single AI agent
The problem
Running parallel Hebrew and English support is one of the most underestimated operational costs in Israeli SMBs. Two scripts to maintain, two sets of training, two queues to staff, and the constant frustration of customers who code-switch mid-call — starting in English, dropping into Hebrew for the technical term, switching back.
Most multilingual AI deployments outside of Israel treat Hebrew as an afterthought — added late, tuned poorly, and noticeably worse than the English experience. Israeli customers can tell within the first three words.
The deployment that works is the inverse: Hebrew-native from day one, with English as a peer language. The agent should be as fluent in technical Hebrew terminology as it is in business English, and should follow the customer wherever the conversation goes.
How Link AI solves it
Link Voice is Hebrew-native. We have spent two years tuning the speech recognition, language model, and synthesis stack specifically for Israeli Hebrew — including the way real Israelis pronounce English brand names and technical terms.
The agent detects the language of the caller's first utterance and continues in it. If the caller switches mid-sentence, the agent switches with them. Hebrew responses sound natural; English responses sound native. Neither feels translated.
All structured outputs (CRM fields, transcripts, summaries) are produced in whichever language you prefer — usually English for internal records and Hebrew for customer-facing artifacts.
Operational impact
Single bilingual stack vs. two language-specific stacks
Customers retire parallel Hebrew and English support tooling, training programs, and team queues — typically reducing the operational overhead of multilingual support by half or more.
What this looks like in practice
A travel agency in Tel Aviv
Serves a mix of Israeli families and English-speaking expat customers. The agent handles both languages on the same phone line, removing the need to maintain two separate booking flows.
An enterprise SaaS company selling globally from Israel
Customers split roughly 60/40 Hebrew/English. Support team previously routed by language, creating wait imbalances. The agent now answers first, routes to a human only when necessary, and language ceases to be a routing variable.
A medical clinic in Jerusalem
Hebrew, English, and a meaningful Russian and French volume. The agent handles Hebrew and English natively and uses a high-quality translation fallback for the long-tail languages — covering 95% of incoming volume with a single deployment.
Frequently asked
- Why not just use a generic multilingual AI?
- Generic multilingual stacks treat Hebrew as a tail language. The result is recognition errors on Israeli accents, awkward synthesis on Hebrew vowel patterns, and tone-deaf responses that sound translated. We tuned the stack on Israeli data — the difference is immediately audible.
- Does it handle code-switching mid-sentence?
- Yes. This is core to the design — Israelis switch languages constantly inside a single sentence, and the agent follows. It will not awkwardly translate a Hebrew brand name into English, and it will not transcribe an English technical term as a phonetic Hebrew approximation.
- What about Arabic?
- Limited support. We can handle Arabic with a reasonable quality bar for transactional flows; for nuanced conversational support we recommend either pure-Arabic deployments tuned specifically, or human escalation.
- Russian, French, other Israeli minority languages?
- We route these to high-quality LLM-driven translation. Quality is acceptable for most service interactions; we mark these conversations clearly in the dashboard so you can monitor.
- Can the agent's tone be different per language?
- Yes. Hebrew responses can be set to 'casual' (default for most Israeli SMBs) or 'formal'; English can be set independently. Most customers run Hebrew casual + English semi-formal.
Related
Written by
Ori Tabachnik
Founder, Link AI
Ori is the founder of Link AI. He works hands-on with Israeli SMBs deploying Hebrew AI voice agents and cold-outreach systems, and writes about what actually moves operational metrics in production.