Incubeta
Ogilvy
National Geographic
Disney
DMA
Oracle
atcore
Airtasker
What is an AI agent?

The engine behind intelligent automation

An AI agent perceives its environment, reasons through a goal, selects the right tools and executes tasks autonomously.

Unlike automation, agents handle unstructured data, adapt to changing conditions and improve over time.

Traditional automation

Rule-based. Breaks on the unexpected.

AI agent

Goal-driven. Adapts and learns over time.

Intelligent and adaptive decision-making

Handles unstructured data and complex tasks

Learns and improves over time

Types of AI agents we build

AI agent categories we build for brands

01.

Conversational assistants

AI agents that engage in natural language, maintain context and provide tailored responses.

Customer support that resolves queries end-to-end

Lead qualification and meeting booking

Internal knowledge agents for teams

02.

Content generation agents

Autonomous agents that research, write and optimize content at scale, consistently on-brand.

Personalised marketing copy at scale

SEO content that researches, writes and optimizes

Social media planning, creation and scheduling

03.

Autonomous decision systems

Agents that monitor, reason and act without waiting for human intervention.

Campaign agents that adjust bids and budgets

SEO monitoring that detects drops and acts

Performance anomaly detection and escalation

Real-life use cases of our AI agent consulting services

AI agents in action across web marketing

01.

Marketing and Content

Personalised content creation

Customised marketing copy and content at scale, tailored to each segment.

SEO optimization assistant

Analyse content, monitor rankings and generate optimization recommendations autonomously.

Social media agent

Plan, write and schedule content across platforms based on performance data.

02.

Content generation agents

Customer interaction chatbot

Engage customers in natural language, understand intent and escalate when needed.

Lead qualification agent

Qualify inbound leads, score intent and route to the right sales rep.

Support resolution agent

Resolve support queries end-to-end without human involvement.

Native AI ecosystems

Platform-specific AI agent solutions

Our AI agents are built natively into your existing business platforms, keeping workflows seamless and operations simple.

Google Agent Space

Enterprise search and AI agents ecosystem that brings together knowledge workers, generative AI and agentic workflows.

Multimodal search across enterprise data
Google Workspace integration
Real-time collaboration

HubSpot AI Agents

Built directly into HubSpot's ecosystem to enhance sales, marketing and customer service without external integrations.

Breeze AI for personalised marketing
Agent.AI network for automation
Native CRM data interaction

Databricks AgentBrick

Research-backed framework to build, evaluate and optimize AI agents grounded in your enterprise data with no-code approaches.

Auto-optimized agent systems
Synthetic data training
Production-ready deployment

What humans decide today, AI will handle tomorrow

How we build

Custom AI agent development services from goals to go-live

01.

Define the goal

We map the goal, tools, data sources and the boundaries within which the agent operates.

02.

Select the right LLM & architecture

Matched to reasoning requirements, latency needs and cost.

03.

Build, tool & test

Connect to your APIs and platforms, build tool-calling logic and test before deployment.

04.

Deploy with guardrails

Human-in-the-loop checkpoints, escalation paths and confidence thresholds on every agent.

05.

Monitor & evolve

Ongoing monitoring, model updates and capability expansion.

06.

Measure impact

Track performance against business goals and refine for real-world outcomes.

Why Mavlers for AI agents

An AI agent development company that delivers outcomes, not demos.

Most AI agent projects fail in production. We build with production reliability as the primary constraint - robust error handling, fallback logic, human escalation paths and ongoing monitoring from day one.

AI-assisted bid management

Real-time bid adjustments to maximise ROAS.

LLM-agnostic

GPT-4o, Claude, Gemini or open-source - the right model for the right task.

Guardrails built in

Human escalation, confidence thresholds and output verification on every agent.

Production-ready from day one

Monitoring, logging and iterative improvement baked in from the start.

Explore how AI automation workflows complement AI agents.

Testimonials

Clients say it better.

We are very pleased to say Mavlers delivered results and consequently we saw marked improvements with overall traffic performance. The level of professionalism and transparency displayed by Mavlers has been impressive and we highly recommend them.

Sandra Field
Simon Reynolds

VP Marketing, Airtasker

Mavlers demonstrated great level of expertise and willingness to go the extra mile to fulfil our requirements. Looking forward to the future projects.

Jordan Racek
Jordan Racek

DHL

From the moment of our first interaction, Mavlers have been courteous, diligent, and effective. I’m very impressed with their work and will certainly be using them again! Thanks guys!

Charlie Burnett
Charlie Burnett

Oracle

Frequently Answered Questions

Everything about our AI agent services

What is the difference between an AI agent and an AI automation workflow?

Workflows follow predefined rules triggered by events. Agents reason through goals, handle unstructured data and adapt to unexpected inputs. Workflows work for structured processes. Agents work for tasks requiring judgement and adaptability.

Which LLMs do you build AI agents on?

OpenAI GPT-4o, Anthropic Claude, Google Gemini and open-source models like Llama and Mistral. Most complex agents use multiple models orchestrated together.

How do you ensure AI agents do not make costly mistakes?

Send us the brief and we will have a certified specialist assigned and working within 48 hours. We plug into your existing workflows, tools and communication channels without lengthy onboarding.

How do you ensure AI agents do not make costly mistakes?

Confidence thresholds, human-in-the-loop checkpoints, escalation paths and output verification. Adversarial testing before deployment, continuous monitoring after. Agents escalate rather than guess outside their competence.

Can you build AI agents inside our existing platforms?

Yes. Natively inside Google Agent Space, HubSpot (Breeze AI and Agent.AI) and Databricks. Also custom agents connecting to your existing CRM, ad platforms and data sources via API.

How long does it take to build and deploy an AI agent?

Simple agents: 2-3 weeks. Multi-tool agents: 4-8 weeks. Enterprise-grade agents: 8-16 weeks. Every project scoped with a clear timeline and milestone plan.

Do you offer white label AI agent development for agencies?

Yes. Discovery, build, testing, deployment and monitoring all delivered under your agency brand.

Your next hire might not be a person.

Expert PPC management under your brand.
Results your clients keep paying for.
Capabilities Deck
Mavlers - Capabilities Deck

400+ specialists. One focused deck.

Services, capabilities, how we work, and what makes Mavlers different - built for marketing leaders and in-house teams who want the full picture fast.

Mavlers - Company Deck
PDF Β· 32 slides Β· mavlers.agency

Work emails only - no Gmail, Hotmail, or Yahoo. We don't spam.

AEO & GEO Audit

Your competitors are showing up in AI answers. You're not.

We run 40 prompts across ChatGPT, Gemini, Perplexity, and Google. We track 5 competitors. We hand you a prioritised report in 4 days - with the exact gaps and fixes.

40 AI prompts tested
5 competitors tracked
12 audit areas
4-day turnaround
Standard
Essentials
$1,200
2 business days
Recommended
Comprehensive
$1,600
3–4 business days
See what's in the auditSee what's in the audit

No retainer. No commitment. Fixed price.