Automated L1 Support

67% of B2B leads
are lost if not answered
within 5 minutes.

Your team cannot maintain a response SLA of seconds at 10 PM on a Tuesday. We design and implement Corporate Chatbots based on Large Language Models (LLMs) strictly trained on your company's knowledge base. 24/7 technical precision with no data hallucinations.

⚠️ Lead leakage mitigation βœ“ RAG Architecture (Own data) πŸ”’ Guaranteed data privacy
Technological Evolution

Moving beyond obsolete
decision tree bots

Traditional chatbots (based on rigid rules and buttons) create friction: if a user asks a question outside the exact script, the system collapses and frustrates the client.

Our assistants use Natural Language Processing (NLP). They understand the context, intent, and semantic nuances of the query, cross-referencing the information with your manuals or internal knowledge bases (RAG Architecture) to deliver resolute answers.

Context injection: responds exclusively with your corporate data.
Semantic understanding: grasps complex variations of the same question.
Uninterrupted 24/7 availability handling massive concurrent peaks.
Escape protocol: routes to a human operator for critical queries.
Demo β€” Private Clinic Assistant
Hi, I wanted to know the price of a dental cleaning and if you take emergencies today.
Hello! A professional dental cleaning costs €65 (it may be covered if you have an associated insurance). Regarding emergencies, yes, our on-call team is available until 20:00h. Would you like me to transfer you to reception to coordinate an urgent visit? 🦷
No emergency needed, but I would like to book the cleaning for Thursday.
Perfect. To process your booking for this Thursday, I am transferring you right now to our admissions team. One moment, please... ⏳
Opportunity Cost

Response latency destroys conversion rates

Traditional Operations
  • βœ— 67% of users without a response in under 5 minutes contact the competition (B2B Data).
  • βœ— Your technical or sales staff spends hours weekly repetitively solving the same Tier 1 questions.
  • βœ— Opportunity leakage: queries generated on weekends or outside working hours go cold.
AI Infrastructure
  • βœ“ First Response Time (FRT) reduced to milliseconds, guaranteeing lead retention.
  • βœ“ Automatic filtering and triage: your human team only intervenes in high-value operations or sales closures.
  • βœ“ Full time coverage without incurring night shift costs or outsourced support.
Suitability Criteria

This deployment is strategic if…

  • β†’

    Your customer service (L1) is saturated by recurring queries and basic operations.

  • β†’

    You offer global services and need to support multiple languages without hiring native agents.

  • β†’

    You handle an extensive volume of technical, legal, or product documentation that clients do not read themselves.

  • β†’

    You seek to qualify leads (Triage) by extracting key variables before assigning the ticket to your sales team.

  • β†’

    You want to centralize data governance and not rely on third-party SaaS plugins that compromise user privacy.

Industry Use Cases

Operational applications of the model

πŸ₯

Healthcare & Clinics

Initial patient triage, resolving doubts about insurance coverage, treatment explanations, and pre/post-op FAQs.

βš–οΈ

Legal Services & B2B

Legal or corporate lead qualification. The assistant extracts the context of the problem before scheduling the consulting session.

πŸ›’

E-commerce

Resolution of shipping policies, returns, product specifications, and sizing guides, mitigating support ticket volume.

🏨

Tourism & Hospitality

Multilingual digital reception: queries about facilities, service hours, cancellation policies, and local guides.

πŸ”§

IT Support & SaaS

Tier 1 incident resolution by ingesting technical documentation or API docs of your software. Escalation to Tier 2 only if necessary.

πŸ“š

Education & Universities

Assistant for prospective students: resolving doubts about study plans, admission requirements, scholarships, and academic calendars.

Service Engineering

Implementation phases (2–4 weeks)

01

Data Ingestion (Data Pipeline)

We collect and structure your company's knowledge corpus (Databases, PDFs, URLs, Manuals) to process it.

02

Vectorization & Embeddings

We transform your documentation into vector representations so the language model (LLM) can search and retrieve the exact information (RAG Architecture).

03

Prompting & Guardrails

We fine-tune the model's behavior: corporate tone of voice, response limits (to prevent hallucinations), and strict human handoff rules.

04

Deployment & Telemetry

Installation on your web infrastructure. We activate a telemetry panel to audit logs, measure the resolution rate, and continuously retrain the model.

Frequently Asked Questions

Chatbot Technical Specifications

We implement a strict RAG (Retrieval-Augmented Generation) architecture. The model is forbidden from using its general knowledge; it only formulates answers by extracting paragraphs from the documentary database we provide.

Unlike SaaS solutions like Tidio or Intercom, our deployment can be isolated on your own infrastructure (Self-Hosted) or dedicated instances, guaranteeing regulatory compliance (GDPR) and industrial secrecy.

Yes. The AI core is channel-agnostic. We can connect the same cognitive brain to a web widget, the official WhatsApp Business API, or channels like Slack and Microsoft Teams for internal support.

We only need to replace or update the source document in the vector database. The bot will acquire the new knowledge in real-time, without requiring code reprogramming.

Yes. Modern LLMs are inherently multilingual. The bot understands the query in the source language (e.g., German), searches for the answer in your documentation (e.g., Spanish), and translates the output to German instantly.

Proof of Concept

Audit your current response capacity

Request a technical meeting. We will evaluate your current support volume and the feasibility of delegating Tier 1 to a cognitive assistant.

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