Conversational AI & Chatbots
Gen AI & Automation / Conversational AI & Chatbots

AI conversations that qualify, convert, and resolve -- 24 hours a day

CRM-connected chatbots and virtual assistants for lead qualification, customer support, and internal knowledge retrieval. Built on your data and your processes -- not a generic widget.

24/7

Always available

<2 min

Avg qualification time

CRM-native

All data synced live

Multilingual

English + regional languages

Executive service questions

Questions leaders ask before approving Conversational AI & Chatbots

This section is written for decision-makers who need to understand the business reason, risk, first step and expected outcome before approving a CRM, data or automation engagement.

Why should leadership prioritise this now?

Conversational AI & Chatbots should become a priority when the current process is limiting revenue visibility, slowing execution or forcing teams into manual workarounds.

  • Leadership cannot get trusted answers quickly
  • Teams rely on spreadsheets outside the CRM
  • Data, reporting or workflow issues are now affecting growth

What is the executive risk of waiting?

Waiting usually increases hidden cost because poor process and data quality compound across reporting, automation, migration and user adoption.

  • Leads go cold while waiting for a human response
  • Support team overwhelmed by repetitive queries
  • Generic chatbots that frustrate rather than help

What should a strong vendor plan include?

A strong plan should connect business goals to architecture, process design, data ownership, implementation sequence, QA and adoption.

  • Current-state diagnosis before build
  • Target operating model and implementation roadmap
  • Validation, reporting and adoption checkpoints

When should a CRO, COO or CRM Director approve this?

Approve the work when the business problem is clear, the cost of inaction is visible and the scope can be tied to revenue, efficiency or governance outcomes.

  • The business owner agrees on the desired outcome
  • The current setup is blocking decisions or execution
  • There is a realistic roadmap and delivery model

What should the first 30 days deliver?

The first 30 days should deliver a decision-ready plan, not vague recommendations.

  • Discovery workshop and system review
  • Risk-ranked issue backlog
  • Implementation roadmap with owners and priorities

What information should you prepare?

Prepare enough context to explain the business impact, current technical state and decision process.

  • Current platform and reporting pain
  • Known data, integration and adoption issues
  • Stakeholders, timeline, budget stage and constraints

Use these answers to decide whether this page matches your current CRM problem. If it does, ask Celumai for a focused audit and implementation plan.

Discuss Conversational AI & Chatbots →

Business challenges

Why Conversational AI & Chatbots projects fail

01

Leads go cold while waiting for a human response

Website visitors who submit a form at 9pm get a response at 9am next morning. By then they have had a discovery call with a competitor. The response time gap is costing pipeline.

02

Support team overwhelmed by repetitive queries

60 to 70% of support tickets are the same 20 questions asked repeatedly. Every one is handled by a human agent who could be solving complex problems instead.

03

Generic chatbots that frustrate rather than help

Off-the-shelf chatbot widgets follow rigid decision trees. The moment a visitor goes off-script the bot fails. Customers hit dead ends and call a human anyway -- more frustrated than before.

04

No CRM integration -- conversations disappear

Chat transcripts live in a separate tool with no connection to the CRM. Sales reps call back with no context. Customers repeat themselves. The conversation history is lost.

What is included

Everything in this service

Lead Qualification Bot

AI-powered qualification bot that engages website visitors, asks structured qualification questions based on your ICP, scores the lead against your criteria, and creates or updates a CRM record in real time -- before a human gets involved.

ICP-based qualification flowDynamic question logicReal-time CRM record creationScored lead handoff

Deliverables

v Qualification conversation flow
v Lead scoring configuration
v CRM integration
v Handoff-to-sales playbook

How it works

Our delivery process

01

Conversation design

Map every conversation flow -- qualification paths, support scenarios, escalation triggers -- before writing a single line of bot logic.

02

Knowledge base build

Train the bot on your product documentation, FAQs, and CRM data. Quality of training data determines quality of responses.

03

CRM integration

Connect the bot bidirectionally to your CRM -- reading context in, writing activities, contacts, and scores out.

04

Testing & tuning

Test against real conversation scenarios, measure intent recognition accuracy, and tune until resolution and qualification rates meet agreed targets.

05

Deployment & monitoring

Deploy to production with real-time monitoring, intent analytics, and a monthly tuning cadence.

Book a free assessment ->

Success stories

Client results

All case studies

Our qualification bot now engages 80% of website leads within 60 seconds of form submission. Lead-to-meeting conversion went from 12% to 31% in the first 90 days. The reps spend their time on meetings, not on following up cold form fills.

H

Head of Marketing

Real Estate Developer

The support bot resolves 58% of incoming queries without any human intervention. Our support team handles the same ticket volume with 30% fewer agents -- and the remaining agents handle harder problems where they add more value.

V

VP Customer Experience

Insurance Company

Case study SaaS & Technology

2.1x increase in qualified demo requests

B2B SaaS Company, Early Growth Stage

A Quick-Win HubSpot Chatbot Rollout That Doubled Qualified Demo Requests

Read case study ->
Case study SaaS & Technology

9 years of customer history migrated with zero disruption to active renewals

B2B SaaS Company, Mid-Market Segment

Migrating a SaaS Company Off a Homegrown CRM Onto Dynamics 365

Read case study ->

Platforms we use for this service

Salesforce Einstein Bots HubSpot Conversations Microsoft Copilot Studio Dialogflow CX Rasa Intercom
Chatbot ROI Calculator

Free resource

Chatbot ROI Calculator -- get it free

Calculate the potential cost savings and lead conversion improvement from deploying a qualification or support bot -- using your own traffic and conversion data.

Excel Calculator * Free

FAQ

Your Conversational AI & Chatbots questions, answered

Ready to start?

Build your conversational AI

We respond within 1 business day with an honest assessment -- no commitment required.

v Response within 1 business day
v Free initial assessment -- no commitment
v Fixed-price options available
v All data under strict NDA from day one
v Milestone-led delivery with clear scope governance

We respond within 1 business day. No spam.

Client results

What this service has delivered

All case studies →
Case Study
MQL-to-SQL conversion 11% → 49%

AI-Powered Lead Scoring That Increased Sales Qualified Lead Accuracy by 340%

B2B Enterprise Software Company

A B2B software company was passing 180 MQLs to sales every month. Conversion to SQL was 11%. Sales…

11%→49%
MQL-to-SQL conversion
68%
Unqualified lead time saved
1.8x
Revenue per rep
Read case study →
Case Study
23 hours weekly manual work eliminated

CRM Automation Programme for a Logistics Company – 14 Manual Processes Eliminated

National Logistics Company

A logistics company with 280 sales and ops staff had 14 manual CRM processes running on spreadsheets and…

14
Manual processes automated
23 hrs
Weekly work eliminated
12%
Renewal conversion increase
Read case study →
Case Study
Contract review 4 days → 2 hours

Document Processing Automation for a Legal Firm – Contract Review Time from 4 Days to 2 Hours

Commercial Law Firm

A commercial law firm reviewing 60 contracts per week was spending 4 days per contract on initial review.…

2 hours
Review time (from 4 days)
94%
Deviation detection accuracy
34%
Associate capacity increase
Read case study →