SmartPath AI
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SmartPath AI
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Resolve More. Escalate Less. Operate Around the Clock.
We build conversational AI bots that handle the majority of your customer and internal support volume autonomously — integrated with your systems, deployed across your channels, and continuously improving on real conversation data.
Support Assistant
● Online · avg reply 4s
70%
Containment
4s
Resp. time
4.7★
CSAT
70%
Support queries resolved without human agent
24/7
Availability across all channels
3.1×
Faster average resolution time
14d
Days to full production deployment
Select a scenario below and run the simulation — see exactly how we classify intent, fetch backend data, and resolve the conversation without human involvement.
TRIGGER: Web chat: 'I want to return order #8821, it arrived damaged'
Intent classified
Order data fetched
Policy check run
Return initiated & label sent
Ticket closed
Every bot we build is trained on your domain, integrated with your systems, and deployed across the channels your customers and teams already use.
Handle the majority of inbound support queries autonomously — FAQs, order status, account lookups, troubleshooting — with natural, on-brand conversation that doesn't feel like a bot.
When a query exceeds the bot's scope, it hands off to a human agent with full conversation context pre-loaded — no customer repeats themselves, no agent starts blind.
A single bot brain deployed across your entire customer surface — website chat, email, Slack, WhatsApp, SMS — with consistent logic and brand voice everywhere.
Bots don't just talk — they act. Retrieve account data, create tickets, update records, and trigger workflows in your CRM and backend systems mid-conversation.
Go beyond reactive support — bots initiate conversations for shipment alerts, renewal reminders, satisfaction surveys, and re-engagement campaigns at the right moment.
Every conversation is a data point. We surface intent trends, unresolved query patterns, and CSAT signals — giving your team intelligence to improve both the bot and human operations.
Three enterprise bot deployments — the support challenge, what we built, and what it delivered.
The Challenge
A direct-to-consumer brand with 400K+ monthly support interactions was running a 74-agent support team handling order status queries, return requests, and product questions. 68% of tickets were identical in nature, but agent capacity during peak seasons was consistently overwhelmed.
What We Built
We deployed a conversational support bot across web chat and email that handles order lookups (live Shopify integration), return initiation, product FAQs, and shipping policy questions autonomously. Complex escalations route to agents with full context — agents handle only the judgment calls.
68%
Tickets resolved without agent
4min→35s
Average first response time
4.7★
Post-resolution CSAT score
$1.4M
Annual support cost reduction
"We scaled through our biggest peak season with the same agent headcount. The bot handled the surge; our team handled the customers who actually needed us."
— VP of Customer Experience
The Challenge
An enterprise software company's IT helpdesk was receiving 2,000+ tickets monthly — password resets, software access requests, VPN issues, and device setup queries — from a 1,800-person workforce. Average ticket resolution time was 2.4 days.
What We Built
We built an internal Slack-based IT support bot that handles the top 40 helpdesk request types autonomously — resetting passwords via Active Directory API, provisioning software access, walking users through VPN setup, and escalating hardware issues to on-site staff with full ticket context.
71%
IT tickets resolved without helpdesk staff
2.4d→18m
Average resolution time
Zero
After-hours helpdesk staffing required
2,000+
Monthly tickets handled automatically
"Our helpdesk team went from reactive ticket processing to proactive system maintenance. The bot handles the volume; they handle the complexity."
— Head of IT Operations
The Challenge
A wealth management firm's client onboarding process required multiple back-and-forth interactions with new clients to collect documents, answer product questions, and schedule advisor calls — a process that averaged 11 days from initial enquiry to first advisor meeting.
What We Built
We deployed a conversational onboarding bot that guides prospective clients through document collection, answers product and fee questions from a curated knowledge base, qualifies clients by AUM and investment profile, and schedules advisor calls directly into the calendar system — all before a human advisor is involved.
11→3
Days from enquiry to advisor meeting
100%
Document collection automated
58%
More qualified leads reaching advisors
2.7×
Advisor capacity increase
"Our advisors now spend their time advising, not chasing documents. The bot qualifies and prepares every client before the first meeting."
— Head of Client Acquisition
Legacy chatbots follow scripts. Ours understand intent — and act on it.
Rule-based chatbots fail on any unexpected phrasing
NLP-based intent models handle natural language variation, typos, and rephrasing gracefully
Bots that can't act force customers to start over with agents
Our bots integrate with your backend — they don't just talk, they retrieve data and trigger actions
No visibility into what customers are actually asking
Full conversation analytics surface intent trends and unresolved query clusters in real time
Chatbot handoffs lose all conversation context
Every escalation transfers the full conversation transcript and classified intent to the receiving agent
From conversation mapping to live deployment — a 4-phase process built for enterprise scale and risk tolerance.
We analyse your existing support tickets, chat logs, and agent scripts to identify the highest-volume intent categories and map the optimal conversation flows for each.
We train intent models on your domain vocabulary and build the knowledge base from your existing documentation, FAQs, and product content.
The bot is integrated with your CRM, helpdesk, and backend systems, then deployed across your chosen channels with brand-aligned conversation design.
Post-launch, we monitor containment rate, CSAT, and unresolved intent patterns — continuously improving the bot and expanding its coverage based on real conversation data.
Tell us your current support volume and your biggest bottleneck. We'll show you what a bot deployment can achieve in your environment within 14 days.