Hire AI that takes on real work in your business
Paloren helps you hire AI: strategy, agents, automation, CRM, voice and training led by Aaron Agius, co-founder, serving businesses worldwide.
Leaders who want to hire AI for operations, sales, service and data work
Paloren builds AI you can hire: a company brain, agents, automation, CRM systems, voice agents and custom apps that take on defined work inside your business. Aaron Agius, an AI implementation consultant, co-founded Paloren with Alex Agius after 20 years building marketing, data and growth systems. First projects run USD 25k to 100k over 2 to 10 weeks.
Hiring AI means giving a system a defined role inside your company, not just buying another software subscription. The system gets a job description: which tasks it owns, which data it reads, which decisions it can make and which it escalates to people.
It gets onboarding, in the form of access to your documents, CRM, call recordings and workflows. And it gets a probation period, where you measure output against the standard a capable person would need to meet.
Paloren treats every engagement this way. A company brain holds institutional knowledge so answers cite your actual policies and history. AI agents handle defined processes end to end.
Workflow automation removes repetitive handoffs. Voice agents answer calls and book appointments. CRM systems with AI keep records clean and surface the next action. Each of these is a hire with a scope, not a demo.
The difference shows up in governance. When you hire AI formally, you decide in advance what it may access, how its work is reviewed and who is accountable when something goes wrong. That structure is what turns experiments into dependable capacity.
The work, made concrete
A hired AI system gets a role, access, guardrails and a review standard
Paloren scopes every build like onboarding a capable team member
Formal hiring turns AI experiments into dependable operating capacity
AI can take on several distinct roles, and Paloren builds each one to a brief. A company brain acts as your institutional memory, answering questions from your documents, policies and past decisions so people stop searching and guessing.
AI agents work like process coordinators, executing multi-step tasks such as qualifying enquiries, drafting responses and updating systems. Workflow automation behaves like a back office assistant, moving data between tools without copy paste errors.
In revenue teams, CRM implementation with AI keeps records current, flags stalled deals and prepares follow ups. On the phone, AI voice agents and receptionists answer callers, capture details and book time around the clock.
A chatbot serves as the front line for common questions on your site. Where nothing off the shelf fits, custom apps give AI a purpose built home. Two supporting hires matter as much as the visible ones.
AI governance sets the rules the rest of the fleet operates under. Team AI training turns your managers into confident directors of the systems you deploy. Paloren delivers all of these as scoped engagements, individually or as a combined program.
| Role AI fills | Paloren service | Investment range | Timeline |
|---|---|---|---|
| Institutional knowledge and answers | Company brain | USD 60k to 150k | 8 to 12 weeks |
| Process execution | AI agents | USD 40k to 90k | 6 to 10 weeks |
| Back office data movement | Workflow automation and integrations | USD 15k to 60k | 3 to 8 weeks |
| Revenue record keeping | CRM implementation with AI | USD 20k to 80k | 4 to 10 weeks |
| Website question handling | AI chatbot | USD 20k to 50k | 4 to 8 weeks |
| Call answering and booking | AI voice agents and receptionists | USD 25k to 60k | 4 to 8 weeks |
| Bespoke internal tooling | Custom apps | From USD 40k | Scoped per build |
published Paloren ranges; final quotes reflect integrations, data condition and governance scope.
Source: Paloren published service ranges
| Engagement | What it produces | Investment | Duration |
|---|---|---|---|
| AI readiness assessment | Ranked view of where AI can take on work safely | From USD 8k | 2 to 3 weeks |
| AI strategy | Roadmap sequencing every AI hire | USD 12k to 25k | 3 to 4 weeks |
| AI governance | Access, review and escalation rules for deployed systems | Quoted at scoping | Set at scoping |
| Team AI training | Managers able to direct and supervise AI systems | Quoted at scoping | Set at scoping |
| Ongoing support | Monitoring, tuning and adjustments after handover | From USD 2,500 per month | 10 hours monthly |
Entry points let you start small before committing to a full build; support keeps systems current after handover.
Source: Paloren published service ranges
| Factor | Effect on scope | Effect on timeline |
|---|---|---|
| Number of integrations | Each additional system connection adds build and test work | Extends testing and handover |
| Condition of your data | Unmanaged documents or CRM records need cleanup before AI reads them | May extend the front of the schedule |
| Governance depth | Stricter access and review rules add configuration and documentation | Adds days around launch |
| Team training needs | More roles to train means more sessions and materials | Training usually runs parallel to build |
These factors explain why two builds of the same service can sit at different points in the published range.
Source: Paloren published service ranges
The work, made concrete
Company brain, agents, automation, CRM, voice and chatbot each map to a distinct role
Governance and training are supporting hires that make the rest safe and effective
Every role is delivered as a scoped engagement with defined boundaries
Companies hire AI to absorb the work that overwhelms their existing teams, not to replace the judgment that makes those teams valuable.
Reporting that used to consume an analyst's Monday, CRM hygiene nobody has time for, call reviews that never happen and content production that stalls between campaigns: these are volume problems.
AI handles volume consistently, at any hour, without losing context between tasks. People remain essential for a different reason. Strategy, relationships, creative direction and edge case decisions need human accountability.
The strongest pattern is a division of labor where AI prepares, drafts, monitors and routes, and people approve, decide and build relationships. The company brain gives new staff answers in minutes instead of days.
Voice agents make sure no caller goes unanswered. Automation keeps systems in sync so nobody retypes the same data three times. Paloren's background shapes this view. Paloren combines implementation, workflow design and practical team training.
The work, made concrete
AI absorbs volume work so teams keep judgment for decisions and relationships
Common first hires: reporting, CRM hygiene, call analysis, content and call answering
Paloren's operating experience grounds every build in real workflows
Paloren starts with an AI readiness assessment, a short engagement from USD 8k over 2 to 3 weeks that examines your data, systems, workflows and appetite for change. The output is a ranked view of where AI can take on work safely and where the foundations need attention first.
Skipping this step is a common reason AI programs stall, because a model connected to messy data produces confident nonsense at scale. If the assessment shows you are ready, an AI strategy engagement follows, typically USD 12k to 25k over 3 to 4 weeks.
This turns the findings into a roadmap: which roles AI takes first, what each one needs, how success is measured and in what order to build. Strategy comes before tools so that every later hire has a purpose.
The first build is deliberately scoped small. A single agent, one automation chain or the first layer of the company brain, delivered in weeks, gives you something real to judge.
From there, expansion follows evidence rather than enthusiasm. This sequence, assess, strategize, build one, then scale, is how Paloren keeps AI hires accountable from day one.
The work, made concrete
Readiness assessment from USD 8k over 2 to 3 weeks comes first
Strategy at USD 12k to 25k turns findings into a build roadmap
The first build stays small so results can be judged quickly
Paloren combines implementation, workflow design and practical team training. Aaron Agius, an AI implementation consultant, stays personally involved in how engagements are scoped and reviewed.
Alex Agius co-leads the company, and the combined team covers strategy, engineering, integration and the governance work that keeps deployments safe.
The work, made concrete
Co-founded by Aaron Agius and Alex Agius
Cost follows what you hire AI to do, how many systems it must touch and how mature your data is. Paloren quotes fixed scopes rather than open ended retainers, so you know the investment before work starts.
A first project generally lands between USD 25k and 100k and runs 2 to 10 weeks, which covers most single role deployments such as one agent, one automation program or a first voice agent.
Entry engagements are priced separately. Readiness assessment starts at USD 8k over 2 to 3 weeks. AI strategy runs USD 12k to 25k over 3 to 4 weeks.
Larger hires cost more because they touch more: a company brain ranges from USD 60k to 150k over 8 to 12 weeks, agents from USD 40k to 90k, CRM implementation with AI from USD 20k to 80k, and custom apps start at USD 40k.
Ongoing support begins at USD 2,500 per month for 10 hours. Three factors move any quote: the number of integrations, the state of your data and how much governance and training wrap around the build.
The tables below list current ranges by service and the factors behind them.
The work, made concrete
First projects typically run USD 25k to 100k over 2 to 10 weeks
Readiness from USD 8k and strategy from USD 12k give lower cost entry points
Integrations, data condition and governance depth drive the final quote
Timelines follow the scope of the hire. Workflow automation delivers fastest, at 3 to 8 weeks, because each chain has clear inputs and outputs. Chatbots and AI voice agents typically run 4 to 8 weeks, CRM implementation with AI takes 4 to 10 weeks, and agents that execute multi-step processes need 6 to 10 weeks.
The company brain is the longest build at 8 to 12 weeks, since it must absorb your documents, connect your systems and be tested against real questions before people rely on it.
Every engagement moves through the same phases: discovery, build, testing against your actual data, team training and handover. Voice agents and chatbots reach usable state early because their scope is narrow.
Company brains and agent fleets take longer because the value compounds across departments, and rushing the knowledge layer produces answers nobody trusts. After handover, ongoing support from USD 2,500 per month for 10 hours keeps systems tuned as your data and processes change.
Paloren serves businesses worldwide, and delivery runs to that standard regardless of where your team sits.
The work, made concrete
Automation lands in 3 to 8 weeks; company brain needs 8 to 12
Every build passes through testing on your real data before handover
Monthly support from USD 2,500 keeps systems tuned after launch
Preparation shortens every timeline that follows. Before Paloren begins, it helps to know where your knowledge lives: which documents hold policy, where the CRM stands, whether call recordings exist and which tools hold customer and operational data.
You do not need perfect data, but you need to know its condition, because the readiness assessment will map it either way. Access matters as much as documentation. Decide early who can grant permissions to the systems AI will touch, and name one accountable owner for the engagement.
That owner should be senior enough to approve data access and process changes without escalation delays. Finally, prepare your people. Hiring AI changes how work flows through a team, and the companies that gain fastest are the ones whose managers ask direct questions during discovery rather than after launch.
Paloren's team AI training exists for exactly this: it gives your staff the vocabulary and judgment to direct the systems once they arrive. Preparation is less about technology and more about clarity over data, access and ownership.
The work, made concrete
Map where documents, CRM records and call recordings live before starting
Name a senior owner who can approve access and process changes
Plan for team AI training so staff can direct the new systems
An AI hire needs management, and AI governance is how Paloren builds that in. Governance defines which systems the AI may read and write, what it must never do without a person, how its outputs are sampled for quality and where an audit trail lives.
These rules are written before launch, not after an incident, so the system operates inside boundaries your leadership has approved. Accountability continues after go live.
Ongoing support from USD 2,500 per month for 10 hours covers monitoring, tuning and adjustments as your data, policies and tools change. When a process evolves, the AI's instructions evolve with it, which prevents the quiet drift that makes unmanaged systems unreliable.
Team AI training completes the structure. People who understand what the system can and cannot do catch problems early, escalate correctly and feed better instructions back into it.
Together, governance, support and training turn a one time build into a managed capability. That is the standard Paloren applies to every deployment, from a single chatbot to a full company brain.
The work, made concrete
Governance sets access, review and escalation rules before launch
Monthly support from USD 2,500 prevents drift as processes change
Training helps people supervise the system and correct it early
Many providers resell a platform and leave you to configure it. The second difference is range.
Strategy, company brain, agents, automation, CRM implementation with AI, voice agents, custom apps, governance, readiness assessment and training are all delivered by the same team, so the pieces fit together instead of accumulating as disconnected tools.
A chatbot built without governance becomes a liability. A company brain without training becomes a shelf. Paloren scopes the surrounding work because the surrounding work is what makes the hire succeed.
The third difference is accountability. Engagements carry defined scopes, published ranges and named leadership. Paloren serves businesses worldwide with one standard of delivery wherever you operate.
The work, made concrete
One team delivers strategy through governance so the pieces fit together
Defined scopes, published ranges and named leadership keep engagements accountable
A short conversation with Paloren establishes what work you want AI to take on, which systems are involved and whether a readiness assessment or a direct scope fits better.
Over 2 to 3 weeks, Paloren maps your data, systems and workflows, then ranks where AI can take on work safely and what foundations need attention first.
An AI strategy engagement turns findings into a sequenced roadmap, then the first hire is scoped with a fixed price range, timeline and success measures.
Paloren builds against your real data, tests with your team, delivers AI training and hands over a system with governance rules in place.
Monthly support keeps the system tuned, and expansion follows evidence, adding agents, automation or company brain layers as results justify them.
| Role AI fills | Paloren service | Investment range | Timeline |
|---|---|---|---|
| Institutional knowledge and answers | Company brain | USD 60k to 150k | 8 to 12 weeks |
| Process execution | AI agents | USD 40k to 90k | 6 to 10 weeks |
| Back office data movement | Workflow automation and integrations | USD 15k to 60k | 3 to 8 weeks |
| Revenue record keeping | CRM implementation with AI | USD 20k to 80k | 4 to 10 weeks |
| Website question handling | AI chatbot | USD 20k to 50k | 4 to 8 weeks |
| Call answering and booking | AI voice agents and receptionists | USD 25k to 60k | 4 to 8 weeks |
| Bespoke internal tooling | Custom apps | From USD 40k | Scoped per build |
published Paloren ranges; final quotes reflect integrations, data condition and governance scope.
Paloren published service ranges
| Engagement | What it produces | Investment | Duration |
|---|---|---|---|
| AI readiness assessment | Ranked view of where AI can take on work safely | From USD 8k | 2 to 3 weeks |
| AI strategy | Roadmap sequencing every AI hire | USD 12k to 25k | 3 to 4 weeks |
| AI governance | Access, review and escalation rules for deployed systems | Quoted at scoping | Set at scoping |
| Team AI training | Managers able to direct and supervise AI systems | Quoted at scoping | Set at scoping |
| Ongoing support | Monitoring, tuning and adjustments after handover | From USD 2,500 per month | 10 hours monthly |
Entry points let you start small before committing to a full build; support keeps systems current after handover.
| Factor | Effect on scope | Effect on timeline |
|---|---|---|
| Number of integrations | Each additional system connection adds build and test work | Extends testing and handover |
| Condition of your data | Unmanaged documents or CRM records need cleanup before AI reads them | May extend the front of the schedule |
| Governance depth | Stricter access and review rules add configuration and documentation | Adds days around launch |
| Team training needs | More roles to train means more sessions and materials | Training usually runs parallel to build |
These factors explain why two builds of the same service can sit at different points in the published range.
A scoped AI system live in your environment, tested against your own data
Governance rules covering access, review and escalation
Team AI training so your people can direct and supervise the system
Documentation of what the system does, what it reads and where it escalates
An ongoing support option from USD 2,500 per month for 10 hours
Signal → Synthesis → System → Scale
Find where intelligence creates value.
Understand the business to identify and prioritize the opportunities with the greatest measurable impact.
Translate complexity into a clear design.
Bring together the people, workflows, data, and technology to define how intelligence should work.
Turn the design into a working capability.
Build the solution that embeds intelligence into how work and decisions happen.
Compound what works.
Measure impact, optimize performance, maintain reliability, and unlock greater leverage.
From signal to scale.
Hiring AI means giving a system a defined role: the tasks it owns, the data it reads, the decisions it can make and the points where it escalates to people. Paloren treats each deployment like onboarding, with access, guardrails, testing and a review standard.
That structure separates a dependable AI hire from a disconnected tool nobody uses.
A first project generally runs USD 25k to 100k over 2 to 10 weeks. Lower cost entry points exist: readiness assessment from USD 8k over 2 to 3 weeks and AI strategy at USD 12k to 25k over 3 to 4 weeks.
Larger builds such as a company brain range from USD 60k to 150k, and ongoing support starts at USD 2,500 per month for 10 hours.
Timelines follow scope. Workflow automation lands in 3 to 8 weeks, chatbots and voice agents in 4 to 8 weeks, CRM implementation with AI in 4 to 10 weeks and agents in 6 to 10 weeks.
A company brain needs 8 to 12 weeks because it must absorb your documents and be tested against real questions before people rely on it.
Paloren was co-founded by Aaron Agius and Alex Agius.
You need to know where your data lives and what condition it is in, not perfection. The AI readiness assessment maps your documents, CRM, call recordings and workflows, then flags what needs repair before a build starts.
Connecting AI to unmanaged data produces confident errors at scale, so Paloren fixes foundations as part of the roadmap rather than pretending they do not matter.
Paloren builds AI to absorb volume work: reporting, CRM hygiene, call handling, content production and repetitive data movement. People keep the work that requires judgment, relationships and accountability.
In practice the strongest pattern is AI preparing, drafting, monitoring and routing while people approve, decide and build relationships. Team AI training helps your staff direct the systems rather than compete with them.
Yes, and that is the recommended path. A single automation chain, one agent, a voice agent or the first layer of a company brain gives you something real to judge within weeks.
First projects generally run USD 25k to 100k over 2 to 10 weeks depending on scope. Expansion then follows evidence, adding roles only where the first hire has proven its footing.
Paloren serves businesses worldwide, and engagements run at country level with one standard of delivery. Discovery, builds, training and support happen through structured remote collaboration, so your team can run the same readiness assessment, strategy and deployment process from any market.
Scope, ranges and timelines stay consistent because the same methodology governs every engagement.
Handover includes governance rules, documentation and training, so your team knows what the system does and where it escalates. Ongoing support from USD 2,500 per month for 10 hours covers monitoring, tuning and adjustments as your data, policies and tools change.
This stewardship prevents quiet drift, the gradual mismatch between a system's instructions and the processes it serves, which is the main reason unmanaged AI stops being useful.
Ready to give AI its first role?
Book a discovery call with Paloren
