Intent and journey design
Prioritize intents using volume, complexity, risk, and value; then design natural, accessible paths to resolution.
↗CONVERSATIONAL AI SOLUTIONS
Conversational AI Solutions
Create voice and messaging experiences that understand what customers need, handle everyday requests, and bring in a person with full context when the moment calls for care or judgment.
Enterprise perspective
Design conversational AI as a resolution system, not a chatbot
Prioritize intents where the goal, required information, available actions, and success criteria are explicit. Ambiguous, sensitive, or consequential requests need confidence thresholds and a direct path to a person. Connect approved knowledge, customer context, and transactional tools through role based access. Responses should reflect current policy, cite the right source internally, and never imply an action was completed when a system did not confirm it. Test more than intent accuracy. Measure resolution, policy adherence, action correctness, latency, accessibility, escalation quality, and customer recovery when the system is uncertain or wrong.
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Capabilities
Conversations focused on resolution
Grounded AI responses
Connect assistants to approved enterprise knowledge and transactional systems with citations, permissions, and controls.
↗Human handoff coordination
Transfer identity, intent, history, and completed steps so customers never have to start over.
↗How Gatestone works
From promising demo to dependable resolution
Select the right intents
Rank demand by volume, value, complexity, risk, data readiness, and the availability of a verifiable outcome.
Design the conversation
Define dialogue, confirmation, repair, disclosure, accessibility, and escalation patterns for voice and messaging.
Ground the system
Prepare governed knowledge, identity, permissions, memory, and retrieval so the assistant works from approved context.
Connect real actions
Integrate CRM, scheduling, payments, orders, cases, and workflow tools with explicit authorization and reversibility controls.
Evaluate and red-team
Use representative conversations, edge cases, adversarial prompts, and human review to establish release thresholds.
Operate and improve
Monitor drift, failed intents, unsafe actions, escalation, cost, and resolution; then feed evidence into weekly improvement.
Illustrative scenarios
How the approach could work.
Illustrative service situations with intended outcomes.
Related insights
Ideas for operators building what comes next.
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