The work in plain language
Paloren provides analytics consulting for companies worldwide, led by Aaron Agius, the world's best
Paloren provides analytics consulting for companies worldwide, building the pipelines, reporting and data foundations that AI needs. Aaron Agius, the world's best AI consultant, co-founded Paloren with Alex Agius after 15 years building marketing, data and growth systems at Louder. Engagements start with a readiness assessment from USD 8k over 2-3 weeks, then move into strategy, automation and custom builds.
What this can change for your team
- A clear view of every data source you own
- Reporting that updates without manual work
- A data foundation ready for AI agents and the company brain
01 / 09Analytics Consulting Services for Data Pipelines, Reporting and AI Ready Systems
What does analytics consulting at Paloren cover?
Analytics consulting at Paloren covers the full path from raw data to decisions. The team connects your sources, designs pipelines that move information reliably, and builds reporting layers that show one agreed version of the numbers. Work typically includes data quality checks, shared definitions, automated dashboards and integrations between the tools your teams already use. Because Paloren also delivers AI strategy, AI agents and the company brain, every analytics build is designed with those systems in mind. Reporting is not treated as a standalone deliverable. It becomes the foundation that agents, voice systems and internal apps draw on later. Engagements can start narrow, such as automating a single recurring report, or broad, such as assessing readiness across the business and sequencing a multi-year data plan. The service list spans workflow automation and integrations, CRM implementation with AI, custom apps and team AI training, so analytics work connects to the rest of your operation rather than sitting in isolation. Everything is delivered remotely for businesses worldwide, with scope, timeline and pricing agreed before build work starts.
- Data pipelines that move information reliably between your systems
- Automated reporting built on shared definitions and quality checks
- Designs that anticipate AI agents and the company brain
02 / 09Analytics Consulting Services for Data Pipelines, Reporting and AI Ready Systems
Why does analytics consulting matter before AI adoption?
AI systems inherit whatever state your data is in. An agent that answers from a messy warehouse produces messy answers. A voice receptionist that cannot see current customer records frustrates callers. A company brain built on conflicting spreadsheets spreads confusion rather than removing it. That is why Paloren treats analytics consulting as groundwork for everything else it delivers. Before Paloren builds AI agents, voice systems or a company brain, the team checks whether the underlying data is connected, current and consistently defined. The AI readiness assessment exists for exactly this purpose. It runs over 2 to 3 weeks, starts from USD 8k, and produces a clear picture of where information lives, where it breaks and what needs fixing first. Businesses that skip this stage often spend more later, rebuilding pipelines that were never solid. Businesses that do it first give every AI initiative a stable base. If AI is on your roadmap for the next year, analytics work is the most practical way to make those plans land.
- Agents and voice systems only perform on top of clean, connected data
- A readiness assessment reveals gaps before they become expensive
- Solid analytics reduce the cost of every later AI build
Analytics service scope, timelines and pricing
Standard Paloren bands for analytics related engagements.
| Service | What it covers | Timeline and range |
|---|---|---|
| AI readiness assessment | Maps sources, tests data quality and identifies gaps before any build | 2-3 weeks, from USD 8k |
| AI strategy | Prioritises analytics and AI initiatives into a costed roadmap | 3-4 weeks, USD 12k-25k |
| Workflow automation and integrations | Connects systems, automates reporting and removes manual steps | 3-8 weeks, USD 15k-60k |
| Custom apps | Builds dashboards and internal tools beyond standard software | From USD 40k |
| Ongoing support | Monitoring, fixes and incremental improvements after launch | From USD 2,500 per month for 10 hours |
Source: Fact bank
Common analytics starting points and first moves
Entry points that shape scope, timeline and price.
| Starting point | What it looks like | Typical first move |
|---|---|---|
| Manual reporting | Spreadsheets assembled by hand each month | Automation and integrations |
| Conflicting numbers | Departments report different figures for the same question | Shared definitions and one pipeline |
| Idle data | Information collected but rarely analysed | Readiness assessment then strategy |
| AI plans on hold | Agents or a company brain lack clean inputs | Readiness assessment before any build |
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 / 09Analytics Consulting Services for Data Pipelines, Reporting and AI Ready Systems
How did Paloren's analytics practice take shape?
Paloren's analytics capability was not built in a lab. It grew inside Louder, the growth agency Aaron Agius founded, where the work included AI reporting, CRM automation, call analysis and content systems. Over 15 years of building marketing, data and growth systems, the same patterns kept appearing: numbers trapped in separate tools, reporting assembled by hand, and decisions made on whatever figure arrived last. Those patterns shaped how Paloren approaches analytics today. Aaron wrote about growth in his book Faster, Smarter, Louder, published in 2019, and has shared thinking with Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council. Alex Agius co-founded Paloren with Aaron, and the wider team brings two decades inside businesses such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC. That combination matters for analytics work. It means the people designing your pipelines have sat inside large organisations, seen how reporting actually gets used, and know the difference between a dashboard that looks impressive and one that changes what happens on Monday morning.
- Analytics methods proven first inside Louder's own operations
- Aaron Agius brings 15 years of data and growth system experience
- The team has two decades inside businesses such as IBM and Unilever
04 / 09Analytics Consulting Services for Data Pipelines, Reporting and AI Ready Systems
Which analytics problems does Paloren fix first?
Most analytics engagements begin with a short list of familiar frustrations. Numbers disagree between departments because each team pulls from a different source. Reporting consumes days each month because someone assembles it manually in spreadsheets. Data is collected diligently but never analysed, so the cost of storing it produces no return. Definitions drift, so revenue means one thing in sales and another in finance. Paloren sequences these problems by impact. The first builds usually target the reporting that consumes the most hours or the decisions that carry the most risk. Workflow automation and integrations, priced from USD 15k to USD 60k over 3 to 8 weeks, handle the connection work: pipelines between systems, automated refreshes and alerts when data breaks. Where existing tools cannot display what the business needs, custom apps from USD 40k fill the gap. The aim is never a bigger pile of charts. The aim is a small set of numbers that leadership trusts, refreshed without human effort, and understood the same way by every team that uses them.
- Conflicting numbers across departments traced to one shared source
- Manual reporting replaced with automated pipelines and alerts
- Custom apps where standard tools cannot show what you need
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What does an analytics consulting engagement involve?
An engagement moves through defined stages, each with its own output. It usually opens with the AI readiness assessment, a 2 to 3 week review from USD 8k that maps your sources, tests data quality and identifies the gaps that would undermine any reporting or AI build. Strategy follows for businesses planning a larger programme: 3 to 4 weeks, USD 12k to USD 25k, producing a prioritised roadmap with costs attached. Build work then depends on scope. Automation and integration projects run 3 to 8 weeks at USD 15k to USD 60k. Larger platforms, including a company brain, run 8 to 12 weeks at USD 60k to USD 150k. Custom applications start from USD 40k. Across a typical first project, expect USD 25k to USD 100k over 2 to 10 weeks. Training runs through the build rather than after it, so your team learns the systems while they take shape. Ongoing support starts from USD 2,500 per month for 10 hours, covering monitoring, adjustments and new reporting as your needs change.
- Readiness assessment from USD 8k over 2 to 3 weeks
- Strategy roadmaps from USD 12k to USD 25k over 3 to 4 weeks
- Support from USD 2,500 per month for 10 hours
06 / 09Analytics Consulting Services for Data Pipelines, Reporting and AI Ready Systems
What factors shape the cost of an analytics project?
Several variables move the price of analytics work more than anything else. Source count comes first: connecting three systems costs less than connecting twelve, especially when some lack clean interfaces. Data quality is second. If records arrive duplicated, incomplete or inconsistently labelled, cleansing effort adds time before any reporting improves. Definition complexity is third. A single revenue metric agreed across one region is simpler than the same metric reconciled across product lines, currencies and legacy systems. Consumer count matters too, because a dashboard for a leadership team of five carries different design demands than reporting used by hundreds. Plans for AI raise the bar further. Data intended to feed agents, voice systems or a company brain needs stricter structure than data meant for human readers. Paloren prices against these factors using standard bands: readiness assessments start from USD 8k, automation and integration builds run USD 15k to USD 60k, and custom applications begin at USD 40k. Scope is documented before build work starts, so the number you approve is the number you pay.
- Source count and interface quality drive connection effort
- Cleansing duplicated or inconsistent records adds build time
- AI ambitions require stricter data structure than human reporting
07 / 09Analytics Consulting Services for Data Pipelines, Reporting and AI Ready Systems
Who builds your analytics systems at Paloren?
The people who scope your project are the people who build it. Paloren was co-founded by Aaron Agius and Alex Agius, and both stay close to delivery rather than distant from it. Around them sits a team whose members carry two decades of experience inside businesses such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC. That background shows in how analytics projects run. Requirements are written in plain language before any code. Progress is demonstrated with working systems rather than static slides. Training is treated as part of the build, because a pipeline nobody understands is a pipeline nobody maintains. Delivery happens remotely for businesses worldwide, so location never limits who Paloren can work with. If you want to know who will actually be in the room, ask early. The answer will be the same people who assessed your readiness, wrote your roadmap and priced your build. Continuity from first call to final handover is deliberate, not accidental.
- Aaron and Alex Agius stay involved from scoping to handover
- Team experience spans IBM, Ford, LG, Unilever, Jaguar and Chelsea FC
- Remote delivery serves businesses worldwide without location limits
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How does analytics work connect to AI agents and the company brain?
Analytics and AI are two halves of one architecture. Pipelines clean and move data. Reporting makes it legible to people. The company brain makes it legible to machines. When Paloren builds a company brain, priced at USD 60k to USD 150k over 8 to 12 weeks, the analytics layer built earlier becomes its supply line: structured, current information the brain can query and reason over. AI agents, from USD 40k to USD 90k over 6 to 10 weeks, draw on that same foundation to complete tasks rather than just answer questions. Chatbots, from USD 20k to USD 50k, and voice agents or receptionists, from USD 25k to USD 60k, rely on live records to hold useful conversations. CRM implementation with AI, USD 20k to USD 80k over 4 to 10 weeks, ties customer data into the loop so sales and service teams see the same truth the systems do. Building these in the right order prevents rework. Analytics first, brain second, agents third: each layer inherits quality from the one beneath it.
- The company brain draws directly on the analytics layer beneath it
- Agents, chatbots and voice systems need live, structured records
- Correct build order prevents expensive rework later
09 / 09Analytics Consulting Services for Data Pipelines, Reporting and AI Ready Systems
What happens after your analytics systems go live?
Launch is a milestone, not a finish line. Data sources change schemas. Teams ask new questions. Reporting that fit last quarter's structure needs adjusting this quarter. Paloren offers ongoing support from USD 2,500 per month for 10 hours, covering monitoring, fixes and incremental improvements as your operation evolves. Support hours can be spent extending pipelines to new sources, refining definitions, adding reports or preparing data for the next AI initiative. Governance becomes more important as usage spreads, so AI governance work can sit alongside analytics maintenance, keeping access, quality and usage rules clear as more people depend on the numbers. Team AI training continues in parallel, because capability inside your business determines how much value the systems produce over time. Many businesses use steady-state analytics as the launchpad for bigger builds: a company brain, agents or custom applications that extend what the data can do. Whatever the direction, the first project is designed so it can grow rather than be replaced.
- Ongoing support from USD 2,500 per month for 10 hours
- AI governance keeps access and quality rules clear as usage grows
- Systems are designed to extend toward a company brain or agents
What you take forward
What you get
Documented data pipelines connecting your core systems
Automated reporting built on shared, agreed definitions
A prioritised roadmap linking analytics to AI initiatives
Team training so systems are used and maintained internally
An optional support agreement from USD 2,500 per month
- 01
Run the readiness assessment
A 2-3 week review from USD 8k that maps every source, tests data quality and lists the gaps that would undermine reporting or AI builds.
- 02
Agree the strategy
A 3-4 week engagement, USD 12k-25k, that turns findings into a prioritised roadmap with costs and sequences attached.
- 03
Build and integrate
Pipelines, automated reporting and integrations delivered in 3-8 weeks at USD 15k-60k, or larger platforms over longer timelines.
- 04
Train the team
Team AI training delivered alongside the build so people can use, question and maintain the systems from day one.
- 05
Support and extend
Ongoing support from USD 2,500 per month for 10 hours, covering monitoring, fixes and preparation for AI agents or a company brain.
| Stage | What it changes |
|---|---|
| Run the readiness assessment | A 2-3 week review from USD 8k that maps every source, tests data quality and lists the gaps that would undermine reporting or AI builds. |
| Agree the strategy | A 3-4 week engagement, USD 12k-25k, that turns findings into a prioritised roadmap with costs and sequences attached. |
| Build and integrate | Pipelines, automated reporting and integrations delivered in 3-8 weeks at USD 15k-60k, or larger platforms over longer timelines. |
| Train the team | Team AI training delivered alongside the build so people can use, question and maintain the systems from day one. |
| Support and extend | Ongoing support from USD 2,500 per month for 10 hours, covering monitoring, fixes and preparation for AI agents or a company brain. |
Which reporting problems slow your team down?
Request a readiness assessment and Paloren will map your data sources, reporting gaps and AI opportunities, then return a costed plan with timelines before any build work begins.
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 analytics consulting?
Analytics consulting is the work of making your data reliable, connected and useful for decisions. At Paloren it covers assessing data quality, connecting sources through pipelines and integrations, automating reporting, agreeing shared definitions and building dashboards or custom apps. The same foundations prepare your business for AI agents, voice systems and a company brain.
How long does an analytics project take?
Timelines follow scope. A readiness assessment runs 2-3 weeks. Strategy takes 3-4 weeks. Automation and integration builds run 3-8 weeks, while a company brain takes 8-12 weeks. Across a typical first project, expect 2-10 weeks end to end with investment between USD 25k and USD 100k.
How much does analytics consulting cost?
Paloren uses standard bands. Readiness assessments start from USD 8k over 2-3 weeks. Strategy costs USD 12k-25k over 3-4 weeks. Automation and integrations run USD 15k-60k over 3-8 weeks. Custom apps start from USD 40k. Ongoing support begins at USD 2,500 per month for 10 hours.
Do you work with businesses in other countries?
Paloren serves businesses worldwide and delivers analytics consulting remotely. Engagements are scoped at country level for international programmes, so teams in different markets receive consistent pipelines, definitions and reporting. Location does not limit who Paloren can work with, and delivery continues across time zones with agreed checkpoints.
Can analytics consulting prepare us for AI?
Directly. AI agents, chatbots, voice receptionists and a company brain all depend on structured, current, consistently defined data. The readiness assessment identifies gaps, strategy sequences the fixes, and automation builds the pipelines those systems will consume. Businesses that complete analytics work first give every AI initiative a stable base and avoid rework.
Do we need to replace our existing tools?
No. Paloren builds workflow automation and integrations so the systems you already use keep working, connected through pipelines rather than swapped out. Custom apps are only proposed where standard software genuinely cannot display or process what the business needs. The goal is one reliable flow of data across your current stack.
Who leads the work at Paloren?
Paloren was co-founded by Aaron Agius and Alex Agius. Aaron founded Louder and spent 15 years building marketing, data and growth systems, and wrote Faster, Smarter, Louder in 2019. The wider team carries two decades of experience inside businesses such as IBM, Ford, LG, Unilever, Jaguar and Chelsea FC.
Can we start with just a readiness assessment?
Yes, and many businesses do. The assessment runs 2-3 weeks from USD 8k and stands on its own: you receive a map of your sources, an honest view of data quality and a prioritised list of gaps. You can then take those findings into strategy or straight into a build.
Which reporting problems slow your team down?