이 페이지는 아직 선택하신 언어로 제공되지 않습니다. 검수를 거친 번역본을 준비하는 동안 영어 버전을 표시하고 있습니다.
개요
Customers and employees expect to ask a question in plain language and get a useful answer. Language models make natural conversation possible; what makes a conversational system useful is its connection to accounts, orders, bookings and knowledge, and its judgment about when to hand the conversation to a person.
We build assistants for web, mobile, messaging and voice channels that combine grounded answers with authenticated transactions, operate within clear policy boundaries, and escalate to human agents with the full conversation and context attached.
비즈니스 활용 분야
- 01
Customer self-service
Answer questions, check order or account status, reschedule appointments and process routine changes through authenticated integrations, available across web chat, mobile apps and messaging channels such as WhatsApp.
- 02
Voice assistants for contact centers
Handle inbound calls with speech recognition and natural voice responses, resolve routine requests, and transfer complex calls to agents along with a summary, so callers do not need to repeat themselves.
- 03
Employee service desks
Resolve HR, IT and facilities requests such as password resets, leave balances and equipment orders by connecting to service management platforms and following approved internal policy.
- 04
Agent assist
Follow live conversations, suggest relevant knowledge and next steps, draft follow-up notes and summarize interactions into the CRM, leaving the human agent in control of every response.
엔지니어링 접근 방식
- 01
Define scope and boundaries
Identify the intents worth automating, the transactions the assistant may perform, the topics it must decline, and the conditions that trigger a handoff to a person.
- 02
Design the conversation
Write the assistant's tone, prompts, clarifying questions and fallback behavior, and prototype flows with real users to find where conversations break down before launch.
- 03
Integrate with systems of action
Connect to CRM, order management, booking and identity systems through secure APIs, with step-up authentication before any account-specific information is shared or changed.
- 04
Engineer the handoff
Integrate with contact center platforms so escalations carry the transcript, detected intent and collected details to the agent, preserving context across channels.
- 05
Evaluate and improve continuously
Review conversation samples, containment and escalation patterns, customer feedback and failure cases, and update knowledge, prompts and test scenarios as products and policies change.
기술 및 플랫폼
Language and speech models
- OpenAI
- Anthropic Claude
- Google Gemini
- Deepgram
- ElevenLabs
- Azure AI Speech
Conversation platforms
- Google Dialogflow CX
- Amazon Lex
- Rasa
- Microsoft Copilot Studio
Channels and contact center
- Twilio
- Amazon Connect
- Genesys Cloud
- WhatsApp Business Platform
- Microsoft Teams
- Slack
Service integration and monitoring
- Salesforce Service Cloud
- Zendesk
- ServiceNow
- OpenTelemetry
- Langfuse
기술 명칭은 각 소유자의 상표이며, 파트너십이나 보증을 의미하지 않습니다.
제공 결과물
- Conversation design covering intents, policies and escalation rules
- Assistant deployed across agreed web, mobile, messaging or voice channels
- Secure integrations with CRM, service and transaction systems
- Human handoff integration with your contact center platform
- Conversation analytics and quality review dashboard
- Test scenario library and content maintenance guide
리더들이 자주 묻는 질문
Will customers know they are talking to AI?
They should, and we design for it. Assistants identify themselves as automated, explain what they can help with and offer a route to a person. Disclosure is good practice and, under rules such as the EU AI Act, increasingly a legal expectation. Your legal team should confirm the specific requirements for your markets.
How do you prevent wrong or off-policy answers?
Answers are grounded in approved knowledge, sensitive topics are routed to people, and guardrails screen both inputs and outputs. We test against scenario libraries that include adversarial prompts and monitor live conversations for failures. Some errors will still occur, so escalation paths and review processes are part of the design from the start.
Can it work with our existing contact center?
In most cases. We integrate with established platforms such as Amazon Connect, Genesys Cloud, Twilio and Salesforce Service Cloud, so the assistant becomes part of your current routing and reporting rather than a separate channel. Platform capabilities vary, and we confirm integration options during discovery.