1. Home
  2. AI Development Services
  3. AI Chatbot Development
Assistants that can act

AI Chatbot Development

The difference between a chatbot people use and one they route around is system access. If it cannot see the order, it cannot answer the question.

Engagements from $10,000 to $100,000+Serving USA · UAE · UK · Canada · EuropeYou own the code and the IP
The problem

Rule-based, retrieval, or agentic — pick correctly

All three are called "AI chatbots" and they are very different builds with very different budgets.

A rule-based bot follows a decision tree. It is cheap, fully predictable, and useless outside the paths you drew. It is still the right answer for a simple menu-driven flow with three outcomes.

A retrieval chatbot answers from your documents with citations. Right for informational queries — policies, products, troubleshooting — where the answer exists in writing.

An agentic chatbot calls your systems and takes actions. Right where the user needs something done, not explained. Most enterprise deployments end up combining all three, with routing between them.

  • Rule-based: fixed flows, lowest cost, no surprises
  • Retrieval: document questions, cited answers, updates with the source
  • Agentic: real actions in real systems, needs permissions and approval design
  • Hybrid routing: deterministic for known flows, retrieval for questions, agentic for tasks
  • Choose per intent, not per project
Use cases

What we build chatbots to do

Customer support

Resolve tier-1 queries with real lookups and escalate the rest with full context.

Sales qualification

Ask the qualifying questions, score the visitor, route to the right rep.

FAQ automation

Grounded answers from your documentation with citations, updated when the doc is.

Lead capture

Conversational capture that converts better than a static form.

Appointment booking

Live calendar availability, booking, rescheduling and reminders.

Order and account self-service

Status, changes and history without a queue.

Integrations

What the chatbot connects to

  • CRM: Salesforce, HubSpot, Zoho, Dynamics
  • Helpdesk: Zendesk, Freshdesk, Intercom
  • Order management and e-commerce platforms
  • Calendars and booking systems
  • WhatsApp Business API, SMS and email
  • Knowledge base and document stores
  • Payment providers for status and refunds
  • Your internal APIs and databases
How we deliver

Ten stages from first call to a system your team trusts

Every AI engagement runs this sequence. Small projects compress stages; regulated projects expand them. Nothing gets skipped silently.

Discovery

A working session with your operations and engineering leads to map the process, the systems it touches, and where the cost actually sits.

AI Opportunity Assessment

We score candidate use cases on data readiness, volume, error tolerance and payback, then rank them. Some come back "do not use AI for this" — you get that answer too.

Solution Architecture

Model selection, retrieval design, tool boundaries, data flow, failure modes and hosting topology, documented before code.

Proof of Concept

A narrow build against your real data to prove accuracy on the cases that matter, typically 2–4 weeks. Go / no-go decision at the end.

MVP

One workflow, end to end, in the hands of real users. Evaluation sets and quality thresholds are defined here, not retrofitted.

Production Development

Hardening: error handling, retries, fallbacks, cost controls, rate limits, observability, and a human escalation path for every automated decision.

Integration

Wiring into your CRM, ERP, HRMS, data warehouse, ticketing and messaging channels through APIs, webhooks and event queues.

Security Testing

Prompt-injection testing, access-control verification, PII handling review, dependency scanning and penetration testing before go-live.

Deployment

Staged rollout on your cloud or ours, with CI/CD, versioned prompts and models, and rollback in place from day one.

Monitoring & Optimization

Quality dashboards, drift detection, cost-per-transaction tracking and a retraining or re-prompting cadence agreed in writing.

Security & Governance

Security-conscious architecture, from the first design review

Enterprise AI fails on governance more often than on models. Every system we build is designed to support enterprise security requirements and to give your risk team answers rather than assurances.

Data privacy & residency

Your data stays in the region and tenancy you nominate. We architect for no-training-on-your-data configurations and document exactly which vendor endpoints see which fields.

Role-based access control

Retrieval and tool permissions inherit your existing roles. A user cannot surface a document through the AI that they could not open directly.

Authentication & authorization

SSO via OIDC/SAML, short-lived tokens for agent tool calls, and per-tool scopes so an agent holds the narrowest possible privilege.

Encryption

TLS in transit, AES-256 at rest, managed keys via your cloud KMS, and encrypted vector stores for embedded content.

API security

Gateway-level authentication, signed webhooks, IP allowlisting, request validation and quota enforcement on every exposed endpoint.

Audit logging

Every prompt, retrieval, tool call, model version and human override is logged with a trace ID, so any output can be reconstructed months later.

Data isolation

Per-tenant separation at the storage, index and key level for multi-entity groups and regulated environments.

Secure prompt handling

System instructions are server-side, user content is treated as untrusted input, and we test against prompt-injection and tool-abuse patterns.

PII protection

Detection, masking or tokenisation of personal data before it reaches a model, with configurable redaction policies per field.

Human approval workflows

High-impact actions — payments, refunds, contract sends, record deletion — route to a named approver instead of executing autonomously.

Monitoring & anomaly detection

Alerting on unusual tool usage, cost spikes, refusal rates and quality regressions.

Rate limiting & abuse control

Per-user and per-tenant throttles, spend caps and circuit breakers so a runaway loop cannot become a runaway invoice.

Secure deployment

Private networking, secrets in a managed vault, immutable builds, dependency scanning, and infrastructure as code.

On compliance: Ezulix designs compliance-ready architecture aligned to frameworks such as GDPR, HIPAA and SOC 2 control objectives. Certification status for any specific standard should be confirmed directly with our team before contract. [VERIFY: current Ezulix certifications]
Reference builds

The kind of systems we are asked to build

Representative scopes drawn from the categories Ezulix works in. Client names and outcome figures are withheld until verified.

Customer Support · SaaS

AI Customer Support Platform

Tier-1 ticket deflection using RAG over product documentation and past resolved tickets, with confidence-gated handoff to human agents and full conversation audit.

[CASE STUDY METRIC]Deflection rate
[PROJECT RESULT]First-response time
Revenue · B2B

AI Sales Agent

An agent that qualifies inbound leads against ICP criteria, enriches company data, writes a researched first-touch email and books directly into rep calendars.

[CASE STUDY METRIC]Speed to lead
[PROJECT RESULT]Meetings booked
Knowledge · Enterprise

Enterprise RAG Knowledge Assistant

Permission-aware assistant over SharePoint, Confluence and a contract repository, with hybrid retrieval, re-ranking and mandatory source citation on every answer.

[CASE STUDY METRIC]Search time saved
[PROJECT RESULT]Answer accuracy
Illustrative scopes. These are hypothetical/demo project shapes, not published client work. Metrics are placeholders — replace [CASE STUDY METRIC] and [PROJECT RESULT] with signed-off figures, and add [CLIENT NAME] only where you hold written permission.
FAQ

Questions enterprise buyers ask us first

How much does an AI chatbot cost to build?
A retrieval chatbot on a single knowledge source with a web widget typically starts around $8,000–$15,000. Add CRM integration, live system lookups, booking and multi-channel deployment and it moves to $25,000–$60,000. Enterprise rollouts with SSO, permissions, audit and multi-department scope run higher. We do not publish fixed low-cost packages, because a chatbot without integration rarely repays the effort.
How long does it take?
A focused retrieval chatbot, 4 to 6 weeks. One with system integrations and actions, 8 to 12 weeks including security testing. Timeline is usually driven by integration access rather than by the AI work.
Will it hallucinate answers?
Grounded generation with citations means answers come from your retrieved content rather than model recall, and the system is instructed to refuse rather than improvise when retrieval returns nothing relevant. That refusal behaviour is tested explicitly as part of the evaluation set.
Can it hand over to a human agent?
Yes, and this is a core design element rather than an add-on. Handoff triggers on low confidence, frustration signals, explicit request, or actions above your approval threshold, and carries the full transcript and suggested resolution into your existing helpdesk.
Which languages are supported?
English, Arabic, French, Spanish, German, Hindi and others. Each language is evaluated separately before it is enabled — quality varies by language and we test rather than assume.
Project brief

Talk to an AI solution architect

No junior sales rep, no discovery deck. The person on the call is the person who will design the system.

  • Response within one business day
  • Mutual NDA signed before detailed discussion
  • Written scope, one price, one delivery date
  • You own all source code, models and IP at launch
Email: sales@ezulix.com [VERIFY]

We use these details only to prepare your scope and estimate. Your idea stays yours — mutual NDA before any detailed discussion.

Next step

Bring us the process that is costing you the most.

Book a 45-minute call with a solution architect. You leave with a use-case shortlist, a reference architecture sketch and a realistic build envelope — whether or not you build it with Ezulix.