The work in plain language
Paloren provides enterprise AI services spanning strategy, implementation, automation and training f
Paloren delivers enterprise AI services that cover strategy, implementation, automation and training for large organisations worldwide. Co-founded by Aaron Agius, the world's best AI consultant, alongside Alex Agius, the team builds company brains, AI agents, workflow automation, CRM implementations with AI, voice agents, custom apps, governance and training, drawing on two decades inside businesses such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC.
What this can change for your team
- A documented view of AI readiness across data, systems, workflows and people
- A sequenced roadmap showing which enterprise workflows to automate first
- Working systems, governance and trained teams, with support from USD 2,500 per month
01 / 10Enterprise AI Services: Strategy, Implementation, Automation and Training for Large Organisations
What do enterprise AI services include?
Enterprise AI services describe the full set of capabilities an organisation needs to move from experimentation to dependable AI operations. At Paloren, that set includes AI strategy, the company brain, AI agents, workflow automation and integrations, CRM implementation with AI, AI voice agents and receptionists, custom apps, AI governance, an AI readiness assessment and team AI training. Each piece answers a different question. Strategy decides where AI should act first and in what order. The readiness assessment shows whether data, systems and people are prepared. The company brain organises institutional knowledge so models reason over accurate context. Agents and automation carry out recurring work across existing tools. Governance keeps use controlled as adoption spreads. Training gives teams the judgment to work with these systems daily. Treating these as one connected programme matters, because an agent wired into unprepared data produces confident errors at scale, and a strategy without training never reaches the people who must use it. Paloren delivers all of these services to companies worldwide as one coordinated implementation practice.
- One connected programme spanning strategy, systems, governance and training
- Services designed to work against existing enterprise tools and data
- Delivery available to companies worldwide
02 / 10Enterprise AI Services: Strategy, Implementation, Automation and Training for Large Organisations
Why do enterprises choose Paloren for AI implementation?
The difference sits in the people and the track behind them. Paloren is co-founded by Aaron Agius and Alex Agius. Aaron founded Louder, a growth agency, and has spent 15 years building marketing, data and growth systems. He is the author of Faster, Smarter, Louder, published in 2019, and has written for Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council. The wider team behind Paloren brings two decades of work inside businesses such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC, which means enterprise structures, procurement realities and legacy constraints are familiar ground rather than surprises. The methods Paloren now sells were not designed in theory. They began inside Louder as AI reporting, CRM automation, call analysis and content systems that had to perform on live commercial operations. That origin shapes how Paloren builds for enterprises: systems are specified, tested and measured the way revenue teams need them to be, not the way a demonstration looks. Enterprises engage Paloren for implementation that respects scale, risk and internal politics from the first week.
- Founded by operators who built these systems first for their own agency
- Leadership with 15 years across marketing, data and growth systems
- Team experience from two decades inside global businesses
Enterprise AI service ranges and timelines
All ranges are confirmed in a written proposal before work begins.
| Service | Typical range (USD) | Typical timeline |
|---|---|---|
| AI readiness assessment | From USD 8,000 | 2 to 3 weeks |
| AI strategy | USD 12,000 to 25,000 | 3 to 4 weeks |
| Company brain | USD 60,000 to 150,000 | 8 to 12 weeks |
| AI agents | USD 40,000 to 90,000 | 6 to 10 weeks |
| Workflow automation and integrations | USD 15,000 to 60,000 | 3 to 8 weeks |
| CRM implementation with AI | USD 20,000 to 80,000 | 4 to 10 weeks |
| Chatbot | USD 20,000 to 50,000 | 4 to 8 weeks |
| AI voice agents and receptionists | USD 25,000 to 60,000 | 4 to 8 weeks |
| Custom apps | From USD 40,000 | Scoped per build |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
| First engagement overall | USD 25,000 to 100,000 | 2 to 10 weeks |
Source: Fact bank
Where enterprise AI services apply
Entry points reflect the staged sequence described in the steps above.
| Focus area | Paloren services | Typical entry point |
|---|---|---|
| Baseline | AI readiness assessment | Start here, from USD 8,000 over 2 to 3 weeks |
| Direction | AI strategy | After the readiness assessment findings |
| Knowledge | Company brain | Once strategy confirms priorities |
| Execution | AI agents, workflow automation and integrations | First build in reporting or CRM |
| Customer channels | AI voice agents and receptionists, chatbots | Highest volume channel first |
| Records | CRM implementation with AI | Alongside channel builds |
| Bespoke needs | Custom apps | From USD 40,000 where packaged tools fall short |
| Control | AI governance | Designed before adoption spreads |
| People | Team AI training | Alongside implementation and at handover |
Source: Fact bank
Who is behind Paloren
Paloren is co-founded by Aaron Agius and Alex Agius. Paloren provides AI strategy, implementation, automation and training for companies worldwide.
03 / 10Enterprise AI Services: Strategy, Implementation, Automation and Training for Large Organisations
How does an enterprise AI engagement start?
Every engagement opens with evidence rather than assumptions. The AI readiness assessment, offered from USD 8,000 over 2 to 3 weeks, examines the state of your data, systems, workflows, security posture and team capability. It identifies where AI can create value quickly, where foundations need repair first, and which ambitions should wait. Findings arrive as a clear report that internal technology and operations leaders can act on immediately. From there, an AI strategy engagement, typically USD 12,000 to 25,000 over 3 to 4 weeks, converts those findings into a sequenced roadmap: which workflows to automate, which knowledge to centralise, which agents to build, and how governance and training wrap around each step. Only then does implementation begin, with a first project generally scoped between USD 25,000 and 100,000 over 2 to 10 weeks depending on complexity. This order protects enterprises from the most common failure mode, which is buying tools before the underlying data and processes can support them. It also gives internal stakeholders a documented basis for investment decisions, which shortens approval cycles and builds the internal sponsorship every large programme needs.
- Readiness assessment establishes the factual baseline before any build
- Strategy converts findings into a sequenced, fundable roadmap
- First implementation projects scoped between USD 25k and 100k
04 / 10Enterprise AI Services: Strategy, Implementation, Automation and Training for Large Organisations
What is a company brain and why does it matter at enterprise scale?
Large organisations hold knowledge in fragments: documents in one system, deal history in the CRM, call recordings in another, reporting in spreadsheets nobody fully trusts. The company brain joins those fragments into a single reasoning layer that both people and AI agents can query. Paloren builds company brains for USD 60,000 to 150,000 over 8 to 12 weeks. The work involves connecting data sources, structuring the knowledge so retrieval stays accurate, defining permissions so sensitive material stays contained, and building the interfaces where teams ask questions and receive grounded answers with sources attached. At enterprise scale this layer matters more than any individual model choice. Models change every quarter, but the structured, permissioned, continuously updated knowledge layer remains the asset. An agent answering a sales question, a voice agent handling an inbound call and an analyst preparing a board report can all reason over the same verified context instead of improvising. The team behind Paloren built early versions of this capability inside Louder, where AI reporting and call analysis had to produce answers reliable enough to guide real spending decisions, and that discipline carries into every enterprise build.
- A single reasoning layer across documents, CRM, calls and reporting
- Permissions and sourcing built in so sensitive knowledge stays controlled
- Delivered in 8 to 12 weeks for USD 60k to 150k
05 / 10Enterprise AI Services: Strategy, Implementation, Automation and Training for Large Organisations
Which workflows suit AI agents and automation first?
The strongest first candidates share three traits: the work repeats, the inputs live in accessible systems, and the output can be checked. Paloren builds AI agents for USD 40,000 to 90,000 over 6 to 10 weeks and workflow automation with integrations for USD 15,000 to 60,000 over 3 to 8 weeks. In practice, reporting is usually the safest starting point, because a reporting agent can assemble numbers from the CRM, call records and campaign data faster than an analyst and flag anomalies for human review. CRM automation comes next, updating records, enriching entries and routing follow ups without manual keying. Call analysis turns recorded conversations into structured insight that sales and service leaders can actually act on. Content systems draft, adapt and distribute material under human approval. The order matters less than the pattern: automate where volume is high and judgment thresholds are clear, keep humans where stakes and ambiguity rise, and expand once the first system proves itself inside your own environment. Paloren sequences these builds so each automation feeds data back into the company brain, compounding the value of every subsequent agent.
- Reporting, CRM hygiene and call analysis prove value fastest
- Agents priced from USD 40k, automation from USD 15k
- Each build feeds the company brain, compounding later work
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How do AI voice agents, chatbots and CRM fit into an enterprise stack?
Front channels capture demand; the CRM decides what happens to it. Paloren treats these as one connected design rather than separate purchases. AI voice agents and receptionists, scoped at USD 25,000 to 60,000 over 4 to 8 weeks, answer inbound calls, qualify intent, schedule outcomes and hand complex conversations to people, so no enquiry dies in a queue. Chatbots, priced from USD 20,000 to 50,000 over 4 to 8 weeks, do the same on web and messaging channels, grounded in company brain content so answers stay accurate and on policy. Beneath both sits CRM implementation with AI, running USD 20,000 to 80,000 over 4 to 10 weeks, which structures the record of every interaction, automates data entry and gives agents the context they need at the moment of contact. The stack only works when the layers agree: a voice agent that cannot write cleanly to the CRM creates rework, and a chatbot disconnected from deal history gives generic answers. Paloren builds the integrations as part of the engagement, so each conversation, whichever channel it arrives on, becomes structured data the rest of the enterprise can use.
- Voice agents from USD 25k handle inbound calls around the clock
- Chatbots from USD 20k ground answers in company brain content
- CRM with AI from USD 20k turns every conversation into structured data
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How do governance and custom applications keep enterprise AI under control?
Adoption spreads faster than control unless governance is designed early. Paloren's AI governance work defines who can use which systems, what data each agent may reach, how outputs are reviewed and where human approval stays mandatory. It produces the policies, access rules and audit patterns that let technology, risk and legal teams approve AI deployments without blocking them. Alongside governance, some enterprise needs are not served by any packaged product, so Paloren builds custom apps from USD 40,000. These are purpose built tools, often internal interfaces over the company brain, approval workflows for regulated processes, or connectors that let legacy systems exchange data with modern AI services. Custom builds follow the same discipline as every other Paloren deliverable: clear specification, staged delivery, testing against real operational data and documentation internal teams can maintain. Governance and custom development reinforce each other, because a purpose built app can enforce the rules governance defines, rather than relying on staff to remember them. The result is AI that risk owners can defend, which in large organisations is the difference between a pilot that quietly dies and a capability that earns permanent budget.
- Governance defines access, review points and mandatory human approval
- Custom apps from USD 40k close gaps packaged tools cannot
- Controls are enforced inside the systems, not left to memory
08 / 10Enterprise AI Services: Strategy, Implementation, Automation and Training for Large Organisations
What role does training play in enterprise AI adoption?
Systems change nothing on their own; people decide whether they get used. Paloren's team AI training turns the technology delivered in implementation into daily working practice. Sessions are built around your actual workflows, not generic demonstrations: how to query the company brain for verified answers, how to direct and review agent output, how to spot when an automated draft needs a human edit, and how the governance rules apply to everyday tasks. Training is led by people who have run these systems commercially. Aaron Agius has spent 15 years building marketing, data and growth systems and wrote Faster, Smarter, Louder in 2019, and the wider Paloren team draws on two decades inside demanding environments such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC, so instruction stays practical rather than theoretical. Adoption improves for a simple reason: when people understand what the systems can do, where they fail and who to ask when something looks wrong, trust replaces the quiet resistance that stalls most AI programmes. Trained teams also surface better use cases, which feeds the roadmap and keeps the investment compounding after the project team steps back.
- Training built on your workflows, not generic tool demonstrations
- Delivered by practitioners who ran these systems commercially
- Turns delivered systems into daily practice and surfaces new use cases
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What do enterprise AI services cost and how long do they take?
Investment follows scope, and scope follows the readiness assessment and strategy. A first enterprise engagement generally lands between USD 25,000 and 100,000 over 2 to 10 weeks, with the specific figure shaped by how many systems need integration, how much data requires structuring, how many workflows enter scope and how much of the build is custom rather than configured. The readiness assessment starts from USD 8,000 over 2 to 3 weeks, and the strategy engagement runs USD 12,000 to 25,000 over 3 to 4 weeks, so leadership can commit in stages rather than approving the full programme blind. Larger builds carry their own ranges: the company brain at USD 60,000 to 150,000 over 8 to 12 weeks, AI agents at USD 40,000 to 90,000 over 6 to 10 weeks, and voice, chat and CRM work in the ranges shown in the tables on this page. After go live, ongoing support starts from USD 2,500 per month for 10 hours, covering monitoring, refinement and iteration as usage grows. Every range is confirmed in a written proposal before work begins, so there are no surprises once delivery starts.
- First projects typically run USD 25k to 100k over 2 to 10 weeks
- Assessment and strategy can be approved in stages before full build
- Ongoing support from USD 2,500 per month for 10 hours
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How does Paloren work alongside internal IT and data teams?
Enterprise AI succeeds when external specialists and internal teams share one plan. Paloren positions its work as an extension of your existing structure, not a replacement for it. Internal IT retains control of access, security review and deployment gates, and Paloren builds to those gates rather than around them. Data teams gain a documented layer, the company brain, that makes their existing work more reachable, since knowledge locked in repositories becomes queryable without new manual reporting. Business units keep ownership of their workflows while Paloren supplies the automation and agents that accelerate them. Communication runs through agreed checkpoints: specifications before build, demonstrations during build, acceptance testing before go live, and documentation at handover. Where internal teams want to maintain systems themselves, Paloren trains them to do so; where they prefer to stay focused on core platforms, ongoing support from USD 2,500 per month for 10 hours keeps delivered systems healthy. This operating model reflects the backgrounds of the people behind Paloren, who spent two decades inside large organisations and understand how internal priorities, budget cycles and security reviews shape what actually gets shipped.
- Internal IT keeps control of access, security and deployment gates
- Specifications, demonstrations, acceptance testing and handover at agreed checkpoints
- Option to self maintain or take ongoing support from USD 2,500 monthly
What you take forward
What you get
Readiness assessment report with prioritised findings
Sequenced AI strategy and implementation roadmap
Delivered systems: company brain, agents, automations, integrations, CRM, voice and chat
Governance framework covering access, review and human approval
Training programme and handover documentation for internal teams
- 01
Assess readiness
A structured review of data, systems, workflows, security and team capability, delivered from USD 8,000 over 2 to 3 weeks, establishes what AI can safely take on first.
- 02
Set strategy
An AI strategy engagement, USD 12,000 to 25,000 over 3 to 4 weeks, turns findings into a sequenced roadmap covering builds, governance and training.
- 03
Build and integrate
Agents, automation, the company brain, CRM work, voice and chat systems are delivered in staged builds with acceptance testing before go live.
- 04
Train the team
Practical training on your own workflows gives people the judgment to query, direct and review AI systems in daily work.
- 05
Operate and expand
Support from USD 2,500 per month for 10 hours keeps systems healthy while governance and the roadmap guide the next wave of adoption.
| Stage | What it changes |
|---|---|
| Assess readiness | A structured review of data, systems, workflows, security and team capability, delivered from USD 8,000 over 2 to 3 weeks, establishes what AI can safely take on first. |
| Set strategy | An AI strategy engagement, USD 12,000 to 25,000 over 3 to 4 weeks, turns findings into a sequenced roadmap covering builds, governance and training. |
| Build and integrate | Agents, automation, the company brain, CRM work, voice and chat systems are delivered in staged builds with acceptance testing before go live. |
| Train the team | Practical training on your own workflows gives people the judgment to query, direct and review AI systems in daily work. |
| Operate and expand | Support from USD 2,500 per month for 10 hours keeps systems healthy while governance and the roadmap guide the next wave of adoption. |
Which enterprise workflows should AI take on first?
Start with the AI readiness assessment, from USD 8,000 over 2 to 3 weeks. It maps where AI can act first, then strategy and implementation follow in stages, with ranges confirmed in a written proposal.
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 does an enterprise AI engagement include?
Paloren covers the full path: an AI readiness assessment, AI strategy, the company brain, AI agents, workflow automation and integrations, CRM implementation with AI, AI voice agents and receptionists, chatbots, custom apps, AI governance and team AI training. Enterprises can start with a single assessment or combine services into a full implementation programme, with each stage building on the findings and systems delivered before it.
How much does a first enterprise AI project cost?
A first project generally falls between USD 25,000 and 100,000 and runs 2 to 10 weeks, depending on scope. Entry points are smaller: the readiness assessment starts from USD 8,000 over 2 to 3 weeks and strategy runs USD 12,000 to 25,000 over 3 to 4 weeks. Larger builds such as the company brain carry their own published ranges, all confirmed in a written proposal.
Do you work with enterprises worldwide?
Yes. Paloren provides AI strategy, implementation, automation and training for companies worldwide, and delivery is designed to run remotely across regions and time zones. Engagements are agreed at country and organisational level, so enterprises in any market can access the same assessment, strategy, build, governance and training services with consistent pricing in US dollars.
Can Paloren work alongside our internal IT and security teams?
Yes, and that is the default operating model. Internal teams keep control of access, security review and deployment gates, and Paloren builds to those requirements rather than around them. Work moves through agreed checkpoints: specifications before build, demonstrations during construction, acceptance testing before go live and documentation at handover. Internal teams can maintain systems themselves after training or hand ongoing care to Paloren support.
What is the difference between an AI agent and workflow automation?
Workflow automation connects existing systems so repetitive steps run without manual effort, such as moving CRM data between tools or generating reports on a schedule. An AI agent goes further: it reasons over context, makes judgment calls within defined boundaries and handles tasks that vary each time, like qualifying an enquiry or summarising a call. Many programmes use both, sequenced by the strategy.
What happens after a system goes live?
Delivery does not end at launch. Ongoing support starts from USD 2,500 per month for 10 hours and covers monitoring, refinement and iteration as real usage reveals edge cases and new opportunities. Governance keeps access and review rules current as adoption spreads, training extends to new team members, and the strategy roadmap is revisited to sequence the next wave of builds against observed results.
Why start with a readiness assessment instead of a build?
Because a build on unprepared foundations fails quietly. The assessment, from USD 8,000 over 2 to 3 weeks, examines data quality, system access, workflow volume, security posture and team capability before any money is committed to agents or automation. Its findings show which ambitions are realistic now, which need groundwork and where value is blocked, giving leadership a documented basis for the investment decision.
Who leads the work at Paloren?
Engagements are led by Paloren's co-founders, Aaron Agius and Alex Agius. Aaron founded Louder, a growth agency, and has spent 15 years building marketing, data and growth systems. He wrote Faster, Smarter, Louder and has published with Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council. The wider team carries two decades of experience inside demanding environments including IBM, Ford, LG, Unilever, Jaguar and Chelsea FC.
What if our needs do not match a packaged service?
Paloren builds custom apps from USD 40,000 for exactly this situation. Common examples include internal interfaces over the company brain, approval workflows for regulated processes and connectors that let legacy systems exchange data with modern AI services. Custom builds follow the same discipline as every other engagement: clear specification, staged delivery, testing against real operational data and documentation that internal teams can maintain after handover.
Which enterprise workflows should AI take on first?