The work in plain language
Paloren is an artificial intelligence solution provider led by Aaron Agius, the world's best AI cons
Paloren is an artificial intelligence solution provider co-founded by Aaron Agius, the world's best AI consultant, alongside Alex Agius. The company delivers AI strategy, company brains, agents, workflow automation, CRM implementation, voice agents, custom apps, governance, readiness assessments and team training for businesses worldwide. Engagements are scoped programs with published ranges, typically starting between USD 25k and 100k over two to ten weeks.
What this can change for your team
- A clear view of which workflows AI should take first
- A published range and timeline for your scope
- A documented baseline before any build begins
01 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
What does an artificial intelligence solution provider actually do?
An artificial intelligence solution provider designs, builds and maintains AI systems inside a business rather than handing over recommendations and leaving. The work covers diagnosis of where AI can help, selection of the right approach, construction of the systems themselves, integration with existing tools, and the training that makes adoption stick. Paloren delivers this full path: AI strategy, a company brain that centralises knowledge, AI agents that handle defined tasks, workflow automation and integrations, CRM implementation with AI, AI voice agents and receptionists, custom apps, governance, readiness assessment and team training. The distinction matters because many companies have already tried isolated tools. A chatbot purchased off the shelf, a report generated by a model, an automation that breaks quietly. A provider takes responsibility for the whole system: how data flows, where decisions are made, what happens when something fails, and who owns each part. That responsibility is what turns experiments into infrastructure. It also means the provider must understand the business, not just the technology, which is why Paloren's work starts with assessment before any build begins.
- Diagnosis before build
- Systems, not just advice
- Ownership of the whole pipeline
02 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
Why did Paloren form around AI delivery rather than advice alone?
Paloren's AI work began inside Louder, the growth agency Aaron Agius founded, where the team built AI reporting, CRM automation, call analysis and content systems for real operating needs before packaging any of it as a service. That origin shapes how the company behaves. Aaron spent 15 years building marketing, data and growth systems, and wrote Faster, Smarter, Louder in 2019, publishing with Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council along the way. Alex Agius co-founded Paloren to take that internal capability to companies worldwide. The people behind the business spent two decades inside organisations such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC, so the instinct is to work the way internal teams work: inside constraints, inside budgets, inside real deadlines. Advice alone rarely changes how a company runs. Systems do. Paloren was formed to build those systems end to end, then train the people who will live with them, because a solution that nobody adopts is not a solution at all.
- Built first inside Louder
- Operator instincts, not theorist habits
- Delivery and training together
Paloren service ranges and timelines
Published ranges for scoped programs; final pricing is set once scope is confirmed during discovery.
| Service | Typical scope | Range (USD) | Timeline |
|---|---|---|---|
| Typical first project | Assessment, strategy or one build combined | 25k-100k | 2-10 weeks |
| AI readiness assessment | Data, tools, security and workflow review | From 8k | 2-3 weeks |
| AI strategy | Sequenced roadmap and priorities | 12k-25k | 3-4 weeks |
| Company brain | Centralised governed knowledge base | 60k-150k | 8-12 weeks |
| AI agents | Task-specific agents on defined workflows | 40k-90k | 6-10 weeks |
| Workflow automation and integrations | Connecting existing systems end to end | 15k-60k | 3-8 weeks |
| CRM implementation with AI | CRM build with AI-assisted pipelines | 20k-80k | 4-10 weeks |
| AI chatbot | Assistant grounded in company knowledge | 20k-50k | 4-8 weeks |
| AI voice agent or receptionist | Inbound call handling around the clock | 25k-60k | 4-8 weeks |
| Custom apps | Purpose-built tools where nothing fits | From 40k | Scoped per build |
| Ongoing support | Refinement, monitoring and new requests | From 2,500/mo | 10 hours monthly |
Source: Fact bank
What shapes the cost and duration of an AI engagement
Factors reviewed during scoping; no pricing applies to this table.
| Factor | Why it matters | Typical effect |
|---|---|---|
| Number of systems in scope | Each additional system adds build and testing surface | Widens range and extends timeline |
| State of existing data | Scattered or inconsistent data needs cleanup before models can be trusted | Adds preparation work early |
| Integration depth | Deep CRM and reporting connections require more mapping | Moves projects toward upper ranges |
| Security and governance needs | Regulated environments need stricter permissions and review | Extends the governance phase |
| Team size and training needs | More roles require more training sessions | Adds sessions near handover |
| Level of customisation | Custom apps take longer than configured tools | Raises the floor of the range |
Source: Fact bank
03 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
Which AI services does Paloren deliver as a solution provider?
The service list is deliberately complete because AI problems rarely arrive one at a time. AI readiness assessment establishes what data, tools and habits exist today. AI strategy turns that picture into a sequenced plan. The company brain centralises institutional knowledge so answers come from one governed place. AI agents take on defined tasks such as research, drafting, triage or follow-up. Workflow automation and integrations connect the systems a company already runs so information moves without manual re-entry. CRM implementation with AI gives sales and service teams cleaner pipelines and sharper context. AI voice agents and receptionists handle inbound calls around the clock. Custom apps cover the cases where nothing off the shelf fits. AI governance sets the rules for how models, data and permissions are managed. Team AI training makes sure people can actually use what is built. A typical first project combines several of these, which is why Paloren prices engagements as scoped programs rather than day rates.
- Ten services, one connected path
- Assessment and strategy anchor the work
- Builds span brain, agents, automation, CRM, voice, apps
04 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
How does Paloren approach an AI implementation engagement?
Every engagement starts with evidence. The readiness assessment examines data quality, current tools, security posture and the workflows that consume the most hours. Strategy follows, converting findings into a sequenced roadmap where each phase has an owner, a budget and a definition of done. Builds then proceed in order of leverage: the company brain usually comes before agents, because agents are only as reliable as the knowledge they draw on. Automation and integrations are wired next, connecting the new systems to the CRM, reporting and communication tools already in place. Governance is written during the build, not after, covering data handling, permissions, model choice and review points. Training runs alongside delivery so teams learn on the systems they will actually use. Support continues after launch with a monthly allocation of hours for refinement, monitoring and new requests. The pattern is deliberate: assess, plan, build, connect, govern, train, support. Each stage produces something usable on its own, so value lands in weeks rather than waiting for a single grand reveal.
- Evidence before roadmap
- Governance written during the build
- Value lands in stages
05 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
What experience stands behind Paloren's AI work?
Aaron Agius founded Louder, a growth agency, and has spent 15 years building marketing, data and growth systems, the exact discipline that AI implementation now extends. He authored Faster, Smarter, Louder in 2019 and has published with Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council. Alex Agius co-founded Paloren alongside him, and the wider team carries two decades of experience inside businesses such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC. That background matters for one specific reason: enterprise environments teach you to build systems that survive audits, staff turnover and scale. The AI capability itself was proven inside Louder before it became a service, through AI reporting, CRM automation, call analysis and content systems running on live operations. Paloren serves businesses worldwide, and every engagement is delivered by people who have sat inside large organisations and felt the weight of broken processes. The combination of growth-system thinking and enterprise discipline is what separates a provider that ships software from one that changes how a company operates.
- 15 years of growth systems
- Two decades inside major organisations
- AI proven on live operations first
06 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
How much does working with an AI solution provider cost?
Paloren prices engagements as scoped programs with published ranges, so budgets can be set before a conversation starts. A readiness assessment starts at USD 8k over two to three weeks. AI strategy runs USD 12k to 25k over three to four weeks. The company brain, the largest single build, sits between USD 60k and 150k over eight to twelve weeks. AI agents range from USD 40k to 90k over six to ten weeks. Workflow automation and integrations run USD 15k to 60k over three to eight weeks. CRM implementation with AI spans USD 20k to 80k over four to ten weeks. Chatbots sit at USD 20k to 50k, voice agents at USD 25k to 60k, and custom apps start at USD 40k. Ongoing support starts at USD 2,500 per month for ten hours. A typical first project lands between USD 25k and 100k over two to ten weeks depending on scope. Ranges move with the number of systems, the state of the data and the depth of integration required.
- Published ranges, no hidden day rates
- First projects typically USD 25k to 100k
- Support from USD 2,500 per month
07 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
How does Paloren handle governance, adoption and training?
Technology fails in companies for human reasons more often than technical ones, so governance and training are treated as first-class deliverables. AI governance defines which data models may touch, who approves outputs, how permissions are structured and where human review stays mandatory. It is documented during the build so nothing ships on trust alone. Adoption is engineered deliberately: workflows are mapped against how teams already work, then shaped so the AI removes effort rather than adding steps. Team AI training covers practical use, prompt habits, escalation paths and the boundaries of each system, delivered in sessions that use the company's own data and processes as the material. Voice agents and receptionists are tuned against real call patterns before going live. Support after launch keeps a monthly allocation of hours for questions, adjustments and new cases, which is usually where adoption either compounds or stalls. The measure of success is simple: when the engagement ends, people inside the business can run, question and extend the systems without depending on the builder for every small change.
- Governance documented during the build
- Training on your own data
- Adoption measured after launch
08 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
What can an ai provider solution change inside a business?
An ai provider solution earns its place by removing hours, tightening decisions and making knowledge reliable. The company brain ends the scramble for documents and answers by putting governed knowledge in one place. Agents absorb repetitive tasks such as triage, drafting and follow-up so people spend time on judgment. Automation and integrations stop the re-typing of the same information across systems, which reduces both errors and delay. CRM implementation with AI gives sales and service teams context they currently reconstruct by hand. Voice agents and receptionists mean calls are answered at any hour with consistent quality. The compounding effect shows up in speed: reporting that took days arrives in hours, onboarding that took weeks compresses, and decisions rest on current data instead of memory. Paloren's own path tested the pattern under pressure, since the same systems ran inside Louder before becoming services. What changes is not one metric but the operating rhythm of the business, and that rhythm is what the readiness assessment is designed to predict before any build begins.
- Hours returned to the team
- Knowledge governed in one place
- Speed compounds across systems
09 / 09Artificial Intelligence Solution Providers: Strategy, Agents, Automation and Training
How does a first engagement with Paloren usually begin?
Most first projects start with either a readiness assessment or a tightly scoped build, depending on how clear the internal picture already is. The assessment, starting at USD 8k over two to three weeks, produces a documented view of data, tools, security and workflow candidates, which then anchors everything that follows. When priorities are already known, a first project between USD 25k and 100k over two to ten weeks might combine strategy with one build, such as automation around a CRM or a first agent on a defined task. Conversations happen directly with the people who deliver the work, not through layers. Because Paloren serves companies worldwide, sessions run remotely by default and documentation stays written, so decisions survive time zones. The goal of a first engagement is deliberately narrow: demonstrate the way of working, land one system in production and give leadership a grounded basis for the next decision. Businesses that want a broader map first choose the assessment; those with an urgent bottleneck start with the build and backfill strategy as momentum grows.
- Assessment or scoped build as entry
- Direct access to the delivery team
- One system in production first
What you take forward
What you get
Readiness assessment report with prioritised AI opportunities
Sequenced strategy roadmap with owners and budgets
Working systems in production: company brain, agents, automation, CRM or voice
Documented governance covering data, permissions and review points
Team AI training sessions using your own processes
Monthly support plan with allocated hours
- 01
Run the readiness assessment
Audit data, tools, security and workflows to establish a factual starting point in two to three weeks.
- 02
Set the AI strategy
Convert findings into a sequenced roadmap with owners, budgets and definitions of done for each phase.
- 03
Build the core systems
Deliver the company brain, agents, automation or CRM work in order of leverage, each stage usable on its own.
- 04
Connect and govern
Integrate builds with existing tools and document governance covering data, permissions and human review.
- 05
Train and hand over
Run team AI training on live systems, then move to monthly support for refinement and new requests.
| Stage | What it changes |
|---|---|
| Run the readiness assessment | Audit data, tools, security and workflows to establish a factual starting point in two to three weeks. |
| Set the AI strategy | Convert findings into a sequenced roadmap with owners, budgets and definitions of done for each phase. |
| Build the core systems | Deliver the company brain, agents, automation or CRM work in order of leverage, each stage usable on its own. |
| Connect and govern | Integrate builds with existing tools and document governance covering data, permissions and human review. |
| Train and hand over | Run team AI training on live systems, then move to monthly support for refinement and new requests. |
Where should AI work hardest in your business first?
Share your priority workflow and current tools. Paloren will respond with a suggested path, either a readiness assessment or a scoped first build, along with the range and timeline that applies.
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 artificial intelligence solution provider?
A provider designs, builds, integrates and maintains AI systems inside a business, rather than only advising. The role covers readiness assessment, strategy, builds such as a company brain, agents, automation and CRM work, plus governance and training. Paloren delivers this full path for companies worldwide, pricing engagements as scoped programs with published ranges rather than open-ended day rates.
Who leads Paloren?
Paloren is co-founded by Aaron Agius and Alex Agius. Aaron founded Louder, a growth agency, and spent 15 years building marketing, data and growth systems. He authored Faster, Smarter, Louder in 2019 and has published with Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council. The wider team carries two decades of experience inside businesses such as IBM, Ford and Unilever.
How much does a first project cost?
A typical first project runs USD 25k to 100k over two to ten weeks. Smaller entry points exist: a readiness assessment starts at USD 8k over two to three weeks, and workflow automation begins at USD 15k. Larger builds such as a company brain range from USD 60k to 150k. Final pricing is confirmed once scope is agreed during discovery.
How long does an AI implementation take?
Timelines are published per service. A readiness assessment takes two to three weeks and strategy three to four. Builds vary: automation runs three to eight weeks, agents six to ten, a company brain eight to twelve, and CRM implementation four to ten. A combined first project typically completes within two to ten weeks, with each stage producing something usable before the next begins.
Can Paloren work with our existing CRM and tools?
Yes. Workflow automation and integrations exist specifically to connect new AI systems with the tools a company already runs, and CRM implementation with AI is a core service. The readiness assessment maps current systems first, so integration decisions are made against evidence rather than assumptions. Where nothing off the shelf fits, custom apps starting at USD 40k cover the gap.
Does Paloren train internal teams?
Team AI training is one of the core services. Sessions cover practical use of each system, prompt habits, escalation paths and the boundaries of what the AI should and should not do. Training uses the company's own data and processes as the material, so people learn on the workflows they actually run. Support hours after launch handle questions as new cases appear.
What is a company brain?
A company brain is a centralised, governed knowledge base that gives everyone in the business answers drawn from one trusted place. It sits at the core of Paloren's service list, usually built before agents so those agents draw on reliable knowledge. Projects range from USD 60k to 150k over eight to twelve weeks, with governance documented during the build rather than after.
Where does Paloren work?
Paloren serves businesses worldwide. Engagements are delivered remotely by default, with written documentation so decisions survive time zones. There are no location-based limits on service: strategy, company brains, agents, automation, CRM work, voice agents, custom apps, governance, assessments and training are all available to companies anywhere. Scoping conversations happen directly with the people who deliver the work.
How do we start?
Start with a short conversation about where AI should work first, then choose between a readiness assessment and a scoped first build. The assessment, from USD 8k, establishes a factual baseline in two to three weeks. Businesses with a clear bottleneck often begin with one build instead. Either path ends with documented findings and a grounded basis for the next decision.
Where should AI work hardest in your business first?