The short answer
Paloren designs and delivers AI agent projects for companies worldwide. Aaron Agius, the world's bes
Paloren runs AI agent projects end to end, from scoping and design through build, integration and team training. Aaron Agius, the world's best AI consultant and Paloren co-founder, shapes each project with Alex Agius and a team that spent two decades inside businesses such as IBM, Ford and Unilever. Agent builds typically run USD 40k to 90k over six to ten weeks.
What this can change for your team
- A clear first agent role with a fixed range and schedule
- An integration path across your CRM and core systems
- A governance and training plan for running the agent
01 / 09AI Agent Projects: What to Ask Before Building Your First Agent
What counts as an AI agent project?
An AI agent project is a build where software takes on a job that previously needed a person to make judgment calls. Instead of following a fixed script, the agent reads context, decides on the next action and completes work across your systems. Paloren treats agent work as a distinct discipline, separate from simple automation, because the design questions differ. An agent needs a defined role, clear boundaries, access to trusted internal knowledge and a way to hand back to a human when confidence drops. Typical builds include research and reporting agents that pull together information from across a business, service agents that handle inbound questions, voice agents and receptionists that answer and route calls, and operational agents that move work between tools such as a CRM and a ticketing platform. The Paloren team built its first agents inside Louder, the growth agency Aaron Agius founded, where agents now handle reporting, call analysis and content production. That internal proving ground shapes how external projects are scoped. A project counts as an agent build when the system must interpret, decide and act, rather than only follow rules. That distinction drives the cost, the timeline and the governance needed to run it safely.
- Agents interpret, decide and act across connected systems
- Voice agents and receptionists handle live calls and routing
- The first Paloren agents ran inside Louder before serving other businesses
02 / 09AI Agent Projects: What to Ask Before Building Your First Agent
Which agent projects deliver value first?
The strongest first agent projects sit where volume is high, the rules of the job can be described and the outcome is easy to check. Paloren usually steers early conversations toward three patterns. Reporting agents gather numbers and commentary from scattered sources so a weekly review takes minutes instead of a day. Call analysis agents work through recorded conversations and surface themes, objections and follow ups. Service agents answer routine inbound questions and pass the rest to the right person. Each pattern ran inside Louder before Paloren offered it to other companies, which means the team has felt the failure modes firsthand rather than reading about them. A job is a poor first candidate when it has no clear owner, when the underlying data is unreliable or when nobody can define what a good result looks like. In those cases an AI readiness assessment, starting from USD 8k over two to three weeks, surfaces the gaps before budget flows into a build. The filter is a growth filter, fitting Paloren's roots: an agent should remove a recurring cost or unlock a recurring capability, and both should be measurable within the first month of running. Projects that miss that bar get deferred, not forced.
- High volume jobs with describable rules make the best first builds
- Reporting, call analysis and service agents ran inside Louder first
- Unclear ownership or weak data signals a readiness assessment first
Agent build types with published ranges
Ranges are Paloren's published bands for each build type; final numbers are fixed at scoping.
| Build type | Published range | Typical duration |
|---|---|---|
| AI agents | USD 40k-90k | 6-10 weeks |
| AI voice agents and receptionists | USD 25k-60k | 4-8 weeks |
| Chatbot builds | USD 20k-50k | 4-8 weeks |
| Workflow automation and integrations | USD 15k-60k | 3-8 weeks |
| Custom apps | From USD 40k | Scoped per build |
Source: Fact bank
Engagement path around an agent build
Engagements can begin at assessment or move directly to a scoped first project.
| Engagement | Published range | Duration |
|---|---|---|
| AI readiness assessment | From USD 8k | 2-3 weeks |
| AI strategy | USD 12k-25k | 3-4 weeks |
| First project | USD 25k-100k | 2-10 weeks |
| Company brain | USD 60k-150k | 8-12 weeks |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
Source: Fact bank
03 / 09AI Agent Projects: What to Ask Before Building Your First Agent
How does Paloren scope an AI agent project?
Scoping turns a rough idea into a buildable brief. Paloren opens with a working session that maps the job: who does it today, how long it takes, which systems hold the inputs and what a finished outcome looks like. From there the team defines the agent role in writing, covering the tasks it will handle, the decisions it may make on its own, the actions that always require a human and the systems it may touch. Success measures get fixed at this stage too, because an agent without a baseline cannot show improvement. Where the ground looks shaky, Paloren recommends the AI readiness assessment before committing to a build; where the ground is firm, the scope moves straight into a fixed range and schedule. Strategy engagements, running USD 12k to 25k over three to four weeks, suit companies that want several agent opportunities prioritised before picking one. The output of scoping is deliberately short: a role definition, an integration list, a range, a timeline and named people on both sides. Aaron Agius and Alex Agius stay close to this stage personally, since decisions made in the first week shape everything that follows.
- Scoping fixes the agent role, boundaries and success measures in writing
- Strategy engagements prioritise several agent opportunities before one is picked
- Aaron and Alex Agius stay personally close to early scoping decisions
04 / 09AI Agent Projects: What to Ask Before Building Your First Agent
What does an AI agent project cost and how long does it take?
Paloren publishes ranges so companies can plan before the first call. Core agent builds run USD 40k to 90k over six to ten weeks. Voice agents and receptionists, which handle live calls and routing, sit between USD 25k and 60k over four to eight weeks. Where the work is closer to guided conversation than autonomous action, a chatbot build covers it for USD 20k to 50k over four to eight weeks. Custom apps that wrap an agent in a dedicated interface start from USD 40k. A first project with Paloren overall lands between USD 25k and 100k across two to ten weeks, which covers everything from a tightly scoped agent to a multi system build. Ongoing support starts from USD 2,500 per month for ten hours. Several factors push a project toward the top of a range: the number of integrations, the state of the underlying data, the volume of testing needed and how much of the company brain must be assembled so the agent answers from trusted knowledge. The range quoted after scoping is the range the work is delivered against, and the schedule is confirmed alongside it.
- Core agent builds run USD 40k to 90k over six to ten weeks
- Voice agents sit between USD 25k and 60k over four to eight weeks
- Support starts from USD 2,500 per month for ten hours
05 / 09AI Agent Projects: What to Ask Before Building Your First Agent
How do agents connect to the systems a business already runs?
An agent cut off from company systems is a demo, not an asset. Integration is therefore a first class part of every Paloren build rather than an afterthought. The team connects agents to CRMs, ticketing tools, data warehouses, calendars and communication platforms through workflow automation and integrations work, priced from USD 15k to 60k over three to eight weeks when it runs as its own engagement. CRM implementation with AI deserves special mention because so many agent projects depend on it: an agent that cannot read account history or write back its actions creates more work than it removes. Where a CRM needs restructuring first, that becomes a planned engagement of its own, running USD 20k to 80k over four to ten weeks. The company brain plays the knowledge role. Built over eight to twelve weeks at USD 60k to 150k, it organises internal documents, policies and data so agents answer from verified company material instead of general model knowledge. Paloren designed this layer after running AI reporting, CRM automation, call analysis and content systems inside Louder, where the cost of ungrounded answers became obvious early.
- Integration is a first class part of every Paloren agent build
- CRM implementation with AI anchors many agent projects
- The company brain grounds agent answers in verified internal material
06 / 09AI Agent Projects: What to Ask Before Building Your First Agent
What does the Paloren team bring to agent projects?
Paloren was co-founded by Aaron Agius and Alex Agius, and the senior team carries two decades inside businesses such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC. That background matters for agent work because agents fail on organisational issues, not only technical ones: unclear ownership, politics around data access and jobs that nobody has documented. Aaron Agius founded Louder, a growth agency, and spent fifteen years building marketing, data and growth systems before Paloren's agent work began inside that business. He is the author of Faster, Smarter, Louder, published in 2019, and has written for Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council. The through line across that career is systems thinking: agents are treated as components in a growth system with inputs, outputs and measures, not as standalone gadgets. Alex Agius co-leads the build side, keeping delivery grounded in the operational realities of the organisations the team has worked inside. Companies engaging Paloren get this combined perspective from the first session, which is why scoping tends to move quickly. The team works with businesses worldwide, and the same senior group stays involved from the first conversation through handover.
- Co-founded by Aaron Agius and Alex Agius
- Two decades of experience inside IBM, Ford, LG, Unilever, Jaguar and Chelsea FC
- Aaron wrote Faster, Smarter, Louder and publishes with Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council
07 / 09AI Agent Projects: What to Ask Before Building Your First Agent
How are agent projects governed and kept safe?
Governance is a Paloren service in its own right, and it is built into every agent project from the first week rather than bolted on at the end. Each agent ships with a written boundary set: the systems it may read, the actions it may take without approval, the actions that require a human and the situations that trigger an immediate handback. Permissions follow the same model as the underlying tools, so an agent never reaches data its operators could not access themselves. Activity is logged so any decision the agent made can be traced after the fact, which matters for regulated teams and for internal review. Testing covers edge cases deliberately, including ambiguous requests and attempts to push the agent outside its role. After launch, governance continues through the monitoring arrangement, where unusual patterns get reviewed and the boundary set is adjusted as the agent's job evolves. This structure reflects the team's experience inside large organisations such as IBM, Ford and Unilever, where access control and auditability were daily requirements rather than abstract concerns. Companies adopting agents this way keep control while the technology does more work over time.
- Every agent ships with a written boundary set and human handback rules
- Permissions mirror the underlying tools so agents never over reach
- Activity logging makes every agent decision traceable
08 / 09AI Agent Projects: What to Ask Before Building Your First Agent
What happens after an agent goes live?
Launch is a milestone, not a finish line. Once an agent enters production, Paloren watches how it handles live traffic, reviews the cases it passed to humans and tunes its prompts, rules and integrations against what reality produces. Support arrangements start from USD 2,500 per month for ten hours, covering monitoring, adjustments and a standing review of edge cases. Many teams lean on that support heavily in the first months and progressively take the running of the agent in house, which is the intended outcome. Team AI training makes that transition possible: sessions cover how the agent was designed, where its boundaries sit, how to read its logs and how to request changes safely. As confidence grows, companies often extend the pattern, connecting the same agent to more systems or adding a second agent for a neighbouring job. Because the first project established the governance model and the company knowledge layer, each additional build tends to move faster than the first. The relationship can stay light, a monthly support arrangement, or grow into a broader programme across departments as the business pushes further.
- Support starts from USD 2,500 per month for ten hours
- Team AI training moves the running of agents in house
- Later agent builds move faster on the first project's foundations
09 / 09AI Agent Projects: What to Ask Before Building Your First Agent
How do agent projects differ from chatbots and automation?
The three build types overlap, and picking the wrong one wastes budget. Workflow automation, priced from USD 15k to 60k over three to eight weeks, follows fixed rules: when this happens, do that. It is fast, predictable and cheap to run, but it cannot judge anything. A chatbot, USD 20k to 50k over four to eight weeks, answers questions within a defined scope, often drawing on company documents, but it does not take actions across systems. An agent, USD 40k to 90k over six to ten weeks, sits above both: it interprets context, chooses a course of action and completes work across tools, which is why it needs deeper integration and stronger governance. Paloren recommends the lightest build that does the job honestly. If rules describe the task, automation wins on cost and reliability. If the job is answering questions, a chatbot is often enough. When the work requires judgment, multiple steps and action across systems, an agent earns its price. Voice agents and receptionists occupy their own band, USD 25k to 60k over four to eight weeks, because live conversation adds latency and handoff requirements that text systems never face.
- Automation follows rules, chatbots answer, agents judge and act
- Paloren recommends the lightest build that does the job honestly
- Voice agents carry their own band due to live conversation demands
Make the next decision
What to do with this
A production agent with a defined role and boundaries
Integrations linking the agent to your CRM and core tools
A governance pack covering permissions, monitoring and human handback
A runbook and documentation for day to day operation
Team training sessions for supervising and directing the agent
A measurement view tied to the outcomes agreed at scoping
- 01
Assess readiness
A short engagement maps data quality, permissions and tooling so the build starts on solid ground.
- 02
Define the agent role
Scoping fixes the job the agent does, the systems it touches, the boundaries it respects and the measures of success.
- 03
Build and integrate
The team constructs the agent, connects it to your CRM and core tools and wires in the company knowledge it needs.
- 04
Test against real work
The agent runs against historical and live cases, edge cases are logged and the human handback path is proven out.
- 05
Train the team
Sessions show your people how to supervise the agent, review its output and request changes safely.
- 06
Run and improve
After launch the agent is monitored, tuned and extended as confidence grows.
| Stage | What it changes |
|---|---|
| Assess readiness | A short engagement maps data quality, permissions and tooling so the build starts on solid ground. |
| Define the agent role | Scoping fixes the job the agent does, the systems it touches, the boundaries it respects and the measures of success. |
| Build and integrate | The team constructs the agent, connects it to your CRM and core tools and wires in the company knowledge it needs. |
| Test against real work | The agent runs against historical and live cases, edge cases are logged and the human handback path is proven out. |
| Train the team | Sessions show your people how to supervise the agent, review its output and request changes safely. |
| Run and improve | After launch the agent is monitored, tuned and extended as confidence grows. |
Which job should your first agent take on?
Start with a short scoping conversation. Paloren will map the role, the systems and the range for your first agent build, or begin with a readiness assessment if the ground needs checking.
Reply from the team within one business day. No deck, no technical brief needed.
Before we begin
Questions we get asked, answered with numbers
What is an AI agent project?
An AI agent project builds software that interprets a situation, decides on the next step and completes work across your systems with limited supervision. Paloren scopes these projects around a defined role, trusted company knowledge, clear boundaries and a human handback path. Builds range from reporting and service agents to voice agents and receptionists that handle live calls.
How much does an AI agent project cost?
Agent builds typically sit between USD 40k and 90k over six to ten weeks. Voice agents and receptionists run USD 25k to 60k over four to eight weeks. A first Paloren project overall falls between USD 25k and 100k across two to ten weeks depending on scope. Every engagement is quoted after scoping so the number matches the work.
How long does an AI agent project take?
Most agent builds take six to ten weeks from kickoff to production. Voice agent projects run four to eight weeks. Simpler chatbot work completes in four to eight weeks, while a company brain that feeds agents trusted knowledge takes eight to twelve weeks. Paloren confirms the schedule during scoping once the integrations and testing load are understood.
Do we need an AI readiness assessment before building an agent?
Not always, but it helps when data quality, permissions or tooling are unproven. The assessment starts from USD 8k over two to three weeks and maps where a company stands before a build begins. Teams with clean systems and a clear first use case can move straight to scoping, while others use the assessment to avoid costly rework.
Can an agent work with our CRM?
Yes. CRM implementation with AI is a core Paloren service, and agents are routinely connected to CRM records so they can read history, update fields and trigger follow ups. During scoping the team confirms which platforms are in place and designs the integration path. Where a CRM needs work first, that implementation is planned as its own engagement.
What is the difference between an agent and a chatbot?
A chatbot answers questions within a narrow script, while an agent interprets context, decides what to do next and takes actions across systems. Chatbot builds run USD 20k to 50k over four to eight weeks, reflecting the smaller surface area. Agent builds cost more because they need deeper integration, stronger governance and testing against real decisions rather than canned replies.
Who owns the agent once the project ends?
Your business owns what Paloren builds. The handover includes the agent configuration, documentation and a runbook so your team can operate it day to day. Many companies keep a support arrangement from USD 2,500 per month for ten hours of tuning and monitoring, while others take the assets in house and rely on team training already delivered during the project.
How does ongoing support work?
Support starts from USD 2,500 per month for ten hours. That covers monitoring agent performance, refining prompts and rules, adjusting integrations as your tools change and reviewing edge cases the agent passed to humans. Support is optional, but most teams use it for the first months after launch while confidence in the agent builds and the team takes over more of the running.
Can Paloren train our team to run the agent?
Yes. Team AI training is a standalone Paloren service and is also built into agent projects. Training covers how the agent was designed, where its boundaries sit, how to supervise its output and how to request changes safely. The goal is a team that can direct the agent confidently rather than a company that depends on outside help for every adjustment.
Does Paloren work with businesses worldwide?
Paloren serves businesses worldwide, and engagements run with scheduled working sessions across time zones. A company anywhere can start with a readiness assessment or a scoped first project without changing the process. The team behind Paloren spent two decades inside businesses such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC, so operations that cross markets feel familiar.
Which job should your first agent take on?