AI services and technical delivery from Dhaka, Bangladesh

REIT Limited

Business Platforms

Customer Support Platform

REIT Limited, a Bangladesh-based AI services and technical-delivery company, configures a support platform that brings knowledge, conversations and case routing into one place for your agents.

What it is

The Customer Support Platform is a configurable service platform that combines support knowledge, customer conversations and case routing. An AI assistant suggests answers from approved knowledge and classifies tickets, while support agents keep control of what is sent and when a case is escalated.

Book an AI AssessmentSee a case study
Illustration of a support conversation with a suggested answer and its source

What problem does a customer support platform solve?

Agents repeat answers that already exist in documents few people can find. The platform suggests an answer with its source for each ticket, classifies and routes cases, and keeps the conversation history in one view. An agent sends every reply.

Support teams answer the same questions repeatedly while the right answer sits in a document few people can find. Tickets are sorted by hand, context is lost when a case changes hands, and customers repeat themselves.

Intended users

  • Support agents, who receive suggested answers with their sources
  • Team leads, who see queues, escalations and unresolved cases
  • Knowledge owners, who approve and update the content the assistant may use

This is a configurable delivery offer, built for each client from agreed modules. It is not an off-the-shelf product, and the view shown on this page is a concept, not a screenshot of a live system.

Which modules does the platform include?

The screens and components a first build would usually include.

Concept view Proposed modules for a configured build. Not a screenshot of an existing product.

How does work move through the platform?

  1. InputCustomer messageA ticket or chat arrives through a supported channel.
  2. ProcessingClassifyCategory and priority are proposed.
  3. ProcessingSuggest an answerA reply is drafted from approved knowledge.
  4. Human approvalAgent decidesThe agent edits, sends or escalates.
  5. OutcomeCase updatedThe ticket and its history are recorded.
Illustrative example How work moves through the platform. It is not a measured client result.

Which channels and systems does it connect to?

The platform connects to the channels and systems listed in this section, where each provides a suitable interface. Every connection is confirmed in the assessment before it is included in scope.

  • Email
  • Web chat
  • Helpdesk tickets
  • WhatsApp Business where an approved interface exists
  • Knowledge articles
  • Product documentation

Intended result

Faster first responses, more consistent answers between agents and shifts, fewer repeat contacts, and a record of which knowledge articles are used or missing.

What result can it produce?

One configured build, with the measures agreed before the pilot and reported after launch.

Case studySample case study

Support agents answer from one knowledge source, with sources shown

Kestrelway Appliances · Online retail, United Kingdom

Customer Support Platform
  • 1.9 hMedian first responsewas 7.2 h
  • 16%Repeat contacts on the same issuewas 24%
  • 74%Suggested answers accepted by agentsnew measure

The problem

Twelve support agents searched four document stores and old tickets to answer warranty and delivery questions. Answers differed between agents and shifts.

What was built

  • A knowledge assistant that suggests an answer with the source passage for each ticket
  • Ticket classification and routing by product line and urgency
  • Escalation to a senior agent with the full conversation context

Where a person approves

An agent sends every reply. The assistant suggests; it does not send, refund or change an order.

The result

Median first-response time fell from 7.2 hours to 1.9 hours, and repeat contacts on the same issue fell by a third.

Systems and tools

  • Helpdesk platform API
  • Email and web chat channels
  • Retrieval index over approved documents
  • Usage and feedback dashboard

Limit found

Suggestions for discontinued products were unreliable until those documents were tagged with end-of-sale dates.

Median first-response time in hourshours
  • Before launch
  • After launch
View data table
Median first-response time in hours (hours)
PeriodValue
May7.4
Jun7.2
Jul7
Aug3.6
Sep2.3
Oct1.9
Sample data
Sector
Online retail
Country
United Kingdom
Size
70 staff
Timeline
Pilot 4 weeks, implementation 8 weeks

What does the published evidence say?

Figures from named surveys and official statistics, each with its source.

66%

of customer service organisations now use agentic AI, up from 39% in 2025.

Salesforce, 20 May 2026Vendor survey of 3,075 service professionals, March to April 2026

30% to 50%

is the share of service cases teams expect AI to resolve, rising from an estimated 30% in 2025 to 50% by 2027.

Salesforce, 10 September 2025Respondent estimates from 6,500 service professionals

87%

of customers say it is essential for companies to provide an option to reach a human agent when using generative AI in customer service.

Gartner, 4 August 2026Survey of 3,566 customers, February to March 2026

How are data, permissions and operation handled?

Data sources
Your helpdesk tickets, approved knowledge articles and, where agreed, product documentation.
Languages
Knowledge assistance in English, and in Bangla where offered and where suitable source content exists.
Permissions
The assistant reads only approved knowledge and may take only the actions listed in the design.
Integrations
Connection to your helpdesk and messaging channels depends on the interfaces they provide; this is checked in the assessment.
Response limits
The design states what the assistant may answer, what it must pass to an agent, and what it must refuse.
Acceptance measures
Agreed before the pilot, for example the share of test tickets classified correctly.
Operation after launch
Knowledge updates, monitoring and changes are handled by your team or through a support arrangement, as the proposal states.

What is the initial scope and what does it cost?

The initial scope is usually one support channel, one knowledge source and one queue. Further channels, languages and reporting views are optional modules agreed in the proposal. The next step is an AI assessment of the process this platform would support.

AI assessment

USD 500

5 working days

One process reviewed for fit, dependencies and risk.

Scoped pilot

from USD 2,500

3 to 4 weeks

One bounded use case built and tested on real cases.

Production implementation

from USD 6,000

6 to 10 weeks

The accepted pilot hardened, connected and launched.

Sample pricesPrices exclude third-party licences, model usage and taxes. The proposal sets the final price for your scope. Invoices are issued in USD; GBP, EUR and AUD are available on request.

Third-party usage and ongoing support are priced separately in the proposal. See How We Work.

Questions buyers ask

Does the assistant reply to customers without an agent?

Not by default. The assistant proposes a reply and a classification, and a support agent decides whether to send, edit or escalate. Sending replies automatically for specific low-risk categories can be agreed later, after the pilot shows how the suggestions perform, and only with written limits.

Is the Customer Support Platform a product we can log into today?

No. It is a configured build, assembled from agreed modules around your helpdesk, knowledge and channels. There is no public demo account. The assessment defines the first scope, and a pilot produces a working version on your own data for you to evaluate.

Discuss this platform for your team

Tell us who would use it, the systems it must connect to and the result you need.

  • Assessment before any build
  • A person approves customer-facing actions
  • Registered in Bangladesh, RJSC No. C-169247/2021
Book an AI AssessmentOr call +880 1711-990010