Voicebots that serve, qualify and resolve in Spanish · sub-second · smart escalation to human
We design and implement enterprise voicebots for Spanish call centres: lead qualification, first-level service, scheduling, post-sale follow-up. With sub-second latency, real backend integration and smart escalation to human agent when it adds value.
We publish this list to qualify together if we fit. If not, we save you time.
We map the 5-10 most frequent conversational flows in current call centre. We audit which backend APIs are accessible (CRM, order management, scheduling, own systems).
Conversational scripts, escalation policies, tone of voice. Functional prototype with Deepgram + Claude/Haiku + ElevenLabs. Testing with internal team.
Connection with CRM, scheduling systems, own backend via API. Automated conversation test suite. Edge case iteration. Observability setup and transcripts.
Gradual deployment: first day 10% of volume supervised by human, weekly scaling to 100%. Metrics of no-escalation resolution, satisfaction, average time.
Invented cases with metrics consistent with our real ranges.
Qualifies budget, timing and need. Books directly with correct broker with brief attached. Immediate escalation if urgency or risk of losing client detected.
Reason for consultation triage, scheduling, voice + WhatsApp reminders with confirmation. Instant slot reassignment if patient cancels.
Queries service status, open incidents, next invoice. Executes simple actions (cancel/reactivate feature). Escalates complexity to correct human agent.
In 2026, with optimised end-to-end streaming architecture (Deepgram + Haiku 4.5 + Cartesia Sonic), average latency from user silence to first audio chunk of response sits between 780 ms and 1,200 ms. Sub-second is achievable in simple flows; in flows requiring real backend query, typically 1-1.8 s.
2 years ago (2024) the same was at 3-5 s. The improvement is dramatic and today the conversation with a well-designed voicebot feels natural. Flows where the bot says "one moment…" can be real-time.
Yes. Typical options: (1) the bot serves first and transfers to human agent in call centre via SIP when it escalates, (2) the bot lives in a parallel IVR and the user chooses, (3) the bot handles alternative channels (WhatsApp voice, webchat) and classic call centre remains for complex calls.
Telephony integration is done via Twilio, Vonage, Retell or native SIP depending on infrastructure. With Genesys and Avaya we work via standard integration APIs.
We design with confidence threshold. If the bot doesn't understand (low recognition threshold) or doubts the information (low response confidence), it escalates immediately to human with full transcript of previous context.
All conversations are recorded (transcript + audio) and audited by random sample by quality team. Errors are labelled and prompts or flow refined. Continuous improvement.
For sensitive actions (service cancellations, financial changes, decisions impacting billing) we always require explicit user confirmation or they pass to human. The bot doesn't make irreversible decisions alone.
Typical pilot (voicebot with 3-5 flows, integration with 2-3 backend systems, Spanish): €25-60k in 8-10 weeks. Monthly operating cost: €500-3,000/month depending on volume (LLM + ASR + TTS + telephony + infra).
Marginal costs per call: €0.08-0.25 typically for 3-5 min calls with standard flow. Very dependent on duration and complexity.
Typical ROI: reduction in call centre operating cost + capture rate improvement from 24/7 service + NPS improvement. Well-designed projects pay off in 6-9 months.
Free 30-min diagnosis with architecture, timing and budget estimate for your specific case.