Data consulting that turns scattered information into AI-ready foundations
Paloren provides data consulting for companies worldwide, from readiness assessments to pipelines, CRM clean-up and the foundations AI needs to perform.
Operations, revenue, data and technology leaders who need trusted data before AI investment
Paloren is a data consulting partner for companies that want their numbers, records and documents ready for AI. Aaron Agius, an AI implementation consultant, co-founded the business with Alex Agius after 20 years building marketing, data and growth systems.
Engagements start with an AI readiness assessment from USD 8,000 over two to three weeks and range to a company brain at USD 60,000 to 150,000.
Data consulting at Paloren means examining how information enters your business, where it settles and how people use it to make decisions. The team maps every source, from CRMs and spreadsheets to call recordings and documents, then identifies the gaps that slow reporting or block automation.
From there, work usually falls into a few streams: cleaning and structuring records, building integrations so systems exchange data without manual copy and paste, and designing reporting people actually trust.
Because Paloren also delivers AI strategy, agents and the company brain, data consulting never happens in isolation. Every pipeline, definition and dashboard is built with the AI you plan to run next in mind.
That matters when a voice agent needs accurate customer records, or when an AI agent answers questions from your internal documents. Paloren combines implementation, workflow design and practical team training.
Engagements begin with an AI readiness assessment, which reviews your systems, data habits and AI opportunities, then produces a prioritized plan you can act on with confidence.
The work, made concrete
Mapping of every data source, flow and owner
Pipelines and integrations that remove manual copy and paste
Reporting structures designed for the AI you plan next
AI systems amplify whatever you feed them. An AI agent answering customer questions retrieves from your documents, so outdated files produce confident but wrong answers. A voice agent booking appointments reads customer records, so duplicate entries create double bookings and frustrated callers.
A company brain surfaces insights across departments, so inconsistent definitions turn every report into an argument. Paloren treats data quality as the first checkpoint of any AI engagement, which is why the AI readiness assessment reviews sources, storage, access rules and definitions before any model work starts.
The team looks for the usual failure points: the same customer recorded in three systems with different details, spreadsheets that only one person understands, exports nobody has reconciled in years, and reports that disagree with each other every month.
Fixing these issues is rarely glamorous, but it is the difference between AI that earns trust and AI that gets abandoned after a month.
| Engagement | What it covers | Duration | Investment (USD) |
|---|---|---|---|
| First project | End-to-end initial engagement | 2-10 weeks | 25,000-100,000 |
| AI readiness assessment | Systems, data flows, reporting and AI opportunity review | 2-3 weeks | from 8,000 |
| AI strategy | Roadmap, priorities and governance design | 3-4 weeks | 12,000-25,000 |
| Workflow automation and integrations | Connections between systems without manual steps | 3-8 weeks | 15,000-60,000 |
| CRM implementation with AI | Structured customer records with AI assistance | 4-10 weeks | 20,000-80,000 |
| Company brain | Unified, governed knowledge foundation | 8-12 weeks | 60,000-150,000 |
| Custom apps | Purpose-built data and AI tools | Scoped per build | from 40,000 |
| Retained support | Ongoing engineering hours after launch | Monthly | from 2,500 for 10 hours |
published ranges for typical Paloren engagements; the readiness assessment ends with a scoped proposal.
Source: Paloren published service ranges
| Data challenge | Paloren service | What changes |
|---|---|---|
| Reports that disagree across departments | Company brain | One governed source with shared definitions |
| Manual spreadsheet assembly every month | Workflow automation and integrations | Pipelines move data between systems automatically |
| CRM records nobody trusts | CRM implementation with AI | Structured records with AI assistance |
| Knowledge locked in documents | Company brain | Searchable, access-controlled knowledge |
| Calls reviewed by nobody | AI voice agents and receptionists | Conversations captured and analyzed |
| Unclear rules for AI use | AI governance | Documented access, privacy and usage rules |
Every recurring challenge has a defined service with scope and range rather than open-ended hours.
Source: Paloren published service ranges
| Parameter | Detail |
|---|---|
| Starting point | AI readiness assessment |
| Typical investment | USD 25,000-100,000 |
| Typical duration | 2-10 weeks |
| Delivery model | Country-level engagement, worldwide |
| After launch | Support from USD 2,500 per month for 10 hours |
Published parameters so you can check fit before any conversation.
Source: Paloren published service ranges
The work, made concrete
AI answers are only as reliable as the data beneath them
Readiness assessment reviews sources, storage, access and definitions first
Clean foundations separate adopted AI from abandoned pilots
Every engagement starts with conversation and ends with systems your team operates without hand-holding. Paloren typically begins with the AI readiness assessment, a two to three week review that examines your current systems, data flows, reporting habits and AI opportunities.
Findings land in a clear report with priorities ranked by impact and effort. If you continue, the next phase turns those priorities into a build plan.
Engineering work then follows what the assessment surfaced: workflow automation and integrations to connect systems that currently pass files by email, CRM implementation with AI to structure customer records, or the company brain to unify knowledge into a single searchable foundation.
Throughout the build, Paloren pairs engineers with your data owners so decisions about definitions and access rules stay with the people who understand the numbers. Delivery closes with documentation, team AI training and, where useful, AI governance guidelines that set rules for how data and models get used.
Ongoing support starts at USD 2,500 per month for ten hours if you want the team to keep improving pipelines after launch.
The work, made concrete
Starts with an AI readiness assessment over two to three weeks
Build phases cover integrations, CRM structure and the company brain
Closes with documentation, training and optional retained support
Certain patterns appear in almost every readiness assessment. Reports disagree because each department pulls numbers from a different system at a different time. Analysts spend the first days of every month assembling spreadsheets by hand.
CRM records decay because salespeople enter data in whatever format suits them. Documents holding pricing, policy and process knowledge sit in folders nobody can search. Customer calls contain objections and buying signals that no one has time to review.
Each of these has a defined fix within the Paloren service set. Workflow automation and integrations move data between systems without manual steps, priced from USD 15,000 to 60,000 over three to eight weeks.
CRM implementation with AI brings structure and assistance to customer records, from USD 20,000 to 80,000. The company brain consolidates documents and knowledge into one governed, searchable place.
The work, made concrete
Conflicting reports traced to competing sources and definitions
Manual monthly reporting replaced by automated pipelines
Unsearchable documents and unreviewed calls turned into usable knowledge
The company brain is Paloren's most data-intensive service, and data consulting is what makes it possible. A company brain unifies your documents, records and institutional knowledge into one governed foundation that AI agents and your people can query.
Before that consolidation can happen, someone has to decide which sources are authoritative, how conflicting versions get resolved, who may access what, and which definitions the whole business will share.
Those decisions are exactly what data consulting produces. In practice, an engagement moves from readiness assessment to source mapping to cleanup, and the company brain build follows once inputs are trustworthy.
The service runs USD 60,000 to 150,000 over eight to twelve weeks, depending on how many sources need consolidation and how much cleanup the assessment uncovers. Companies that skip the data preparation phase usually end up rebuilding, because an AI agent retrieving from messy inputs produces answers nobody defends.
Aaron Agius and Alex Agius co-founded Paloren to deliver this sequence end to end, so the same team that assesses your data also builds and maintains what follows. Builds favor the systems your teams already use, so people adopt new capabilities inside familiar tools rather than through a forced migration.
The work, made concrete
The company brain unifies documents, records and knowledge in one governed place
Data consulting settles authoritative sources, definitions and access first
Builds run USD 60,000 to 150,000 over eight to twelve weeks
Paloren was co-founded by Aaron Agius, an AI implementation consultant, and Alex Agius, and the pairing matters for data work specifically. That background means data consulting at Paloren starts from revenue reality: pipelines exist to serve decisions about growth, not to win architecture debates.
Paloren combines implementation, workflow design and practical team training. The result is advice delivered by operators rather than theorists.
The work, made concrete
Co-author of Faster, Smarter, Louder, published with Entrepreneur, Salesforce, HubSpot and the Forbes Agency Council
Team experience from IBM, Ford, LG, Unilever, Jaguar and Chelsea FC
Deliverables in a Paloren engagement are working assets, not slide decks that gather dust. The AI readiness assessment produces a written report covering your current systems, data flows, risks and AI opportunities, plus a ranked list of what to fix first.
Strategy work converts that into an AI roadmap with sequenced initiatives, governance principles and success measures. Build phases hand over the pipelines, integrations, dashboards and CRM structures themselves, running in your environment with your team holding the keys.
Documentation covers how each flow works, where data travels and who owns which definition, so knowledge does not leave with the project. Team AI training sessions teach your people to operate the new systems, question the outputs and spot data issues before they spread.
Where required, AI governance guidelines document the rules for access, privacy and appropriate use. Everything ships with the assumption that your people, not Paloren, run the systems day to day, and support from USD 2,500 per month for ten hours exists for teams that want continued engineering attention.
The work, made concrete
Readiness report with ranked priorities and AI opportunities
Pipelines, integrations and dashboards running in your environment
Documentation, training sessions and governance guidelines for handover
Pricing follows scope, and Paloren publishes ranges so you can sanity-check fit before a call. A first project typically lands between USD 25,000 and 100,000 and runs two to ten weeks.
The AI readiness assessment, which most engagements start with, comes in from USD 8,000 over two to three weeks.
Larger data foundations such as the company brain range from USD 60,000 to 150,000 over eight to twelve weeks, while workflow automation and integrations run USD 15,000 to 60,000 and CRM implementation with AI sits between USD 20,000 and 80,000.
Custom apps start at USD 40,000 where your data needs a purpose-built tool. Retained support begins at USD 2,500 per month for ten hours. Where a project lands inside these ranges reflects the number of systems involved, the volume of cleanup required and how much of the build reuses patterns the team has shipped before.
The readiness assessment exists partly to remove guesswork here: after two to three weeks you receive a scoped proposal rather than a ballpark.
The work, made concrete
First projects typically run USD 25,000 to 100,000 over two to ten weeks
Readiness assessment from USD 8,000 over two to three weeks
Assessment ends with a scoped proposal, not a vague ballpark
Choosing a data consulting partner comes down to evidence you can verify. Look for a team that has run data systems inside real operations, not only advised on them. Second, check whether the firm builds what it recommends.
Paloren delivers the full service set, from AI strategy and the company brain to agents, automation, CRM implementation, voice agents, custom apps and governance, so recommendations never stop at a slide deck.
Third, ask how knowledge transfers. Training is a core Paloren service because data foundations fail when only the builder understands them. Fourth, confirm the delivery model fits your geography: Paloren serves businesses worldwide with country-level engagement rather than office networks.
Finally, treat published ranges and a structured readiness assessment as signs of a partner that scopes honestly before asking for a larger commitment.
The work, made concrete
Operating history inside IBM, Ford, LG, Unilever, Jaguar and Chelsea FC
One team advises, builds, trains and supports after launch
Worldwide delivery scoped at country level with published ranges
A short call establishes which data problems hurt most and whether Paloren fits before any commitment.
Over two to three weeks, Paloren reviews systems, data flows, reporting habits and AI opportunities, from USD 8,000.
Findings become a prioritized plan with sequenced initiatives, owners and success measures, within the USD 12,000-25,000 strategy range where required.
Engineers deliver pipelines, integrations, CRM structure or the company brain in your environment, with your data owners involved at every decision.
Team AI training, governance guidelines and optional retained support from USD 2,500 per month keep systems healthy after launch.
| Engagement | What it covers | Duration | Investment (USD) |
|---|---|---|---|
| First project | End-to-end initial engagement | 2-10 weeks | 25,000-100,000 |
| AI readiness assessment | Systems, data flows, reporting and AI opportunity review | 2-3 weeks | from 8,000 |
| AI strategy | Roadmap, priorities and governance design | 3-4 weeks | 12,000-25,000 |
| Workflow automation and integrations | Connections between systems without manual steps | 3-8 weeks | 15,000-60,000 |
| CRM implementation with AI | Structured customer records with AI assistance | 4-10 weeks | 20,000-80,000 |
| Company brain | Unified, governed knowledge foundation | 8-12 weeks | 60,000-150,000 |
| Custom apps | Purpose-built data and AI tools | Scoped per build | from 40,000 |
| Retained support | Ongoing engineering hours after launch | Monthly | from 2,500 for 10 hours |
published ranges for typical Paloren engagements; the readiness assessment ends with a scoped proposal.
Paloren published service ranges
| Data challenge | Paloren service | What changes |
|---|---|---|
| Reports that disagree across departments | Company brain | One governed source with shared definitions |
| Manual spreadsheet assembly every month | Workflow automation and integrations | Pipelines move data between systems automatically |
| CRM records nobody trusts | CRM implementation with AI | Structured records with AI assistance |
| Knowledge locked in documents | Company brain | Searchable, access-controlled knowledge |
| Calls reviewed by nobody | AI voice agents and receptionists | Conversations captured and analyzed |
| Unclear rules for AI use | AI governance | Documented access, privacy and usage rules |
Every recurring challenge has a defined service with scope and range rather than open-ended hours.
| Parameter | Detail |
|---|---|
| Starting point | AI readiness assessment |
| Typical investment | USD 25,000-100,000 |
| Typical duration | 2-10 weeks |
| Delivery model | Country-level engagement, worldwide |
| After launch | Support from USD 2,500 per month for 10 hours |
Published parameters so you can check fit before any conversation.
AI readiness report with ranked priorities
Data flow map covering sources, owners and definitions
Working pipelines, integrations and dashboards in your environment
Documented access rules and AI governance guidelines
Team AI training sessions for the people who run the systems
Data consulting examines how information enters your business, where it lives and how reliably people can use it. At Paloren it covers source mapping, cleanup, integrations, reporting design and the preparation AI needs.
Because Paloren also builds agents, automation and the company brain, every recommendation accounts for what you plan to run on that data next.
A first project typically runs USD 25,000 to 100,000 over two to ten weeks. Most engagements begin with an AI readiness assessment from USD 8,000 over two to three weeks, which ends in a scoped proposal.
Larger foundations such as the company brain range from USD 60,000 to 150,000, and retained support starts at USD 2,500 per month for ten hours.
The readiness assessment takes two to three weeks. Strategy work runs three to four weeks. Build phases vary by scope: automation and integrations take three to eight weeks, CRM implementation four to ten weeks, and the company brain eight to twelve weeks.
A first project overall usually completes within two to ten weeks depending on how many systems are involved.
Rarely. Paloren builds integrations and automation around the systems you already run, so data flows between tools instead of through spreadsheets and email. Migrations only enter the plan when an assessment shows a platform genuinely cannot support what you need.
The default approach keeps your team inside familiar tools while the data layer underneath improves.
Yes. CRM implementation with AI is a core Paloren service, running USD 20,000 to 80,000 over four to ten weeks, and it includes structuring records, automating updates and adding AI assistance.
Engagements include AI governance work that documents access rules, privacy expectations and appropriate use before systems go live. Data stays in your environment wherever practical, and build access is limited to the people actively working on it.
Paloren combines implementation, workflow design and practical team training.
Paloren serves businesses worldwide. Engagement happens at country level, which means scoping, delivery and support are organized around your country rather than a physical office network.
Discovery calls, assessments and build phases run remotely with structured checkpoints, and training equips your people locally. Geography affects scheduling more than it affects scope or pricing ranges.
You receive documentation, trained people and systems your team operates daily. If you want continued attention, retained support starts at USD 2,500 per month for ten hours and covers pipeline monitoring, improvements and new automation as needs emerge.
Many businesses also return for later phases, such as AI agents or a company brain, once earlier foundations prove themselves.
AI consulting decides what to build with AI and in what order. Data consulting makes sure the information underneath is accurate, connected and governed so those builds succeed.
At Paloren the two are sequenced deliberately: the readiness assessment examines data and AI opportunity together, then strategy and engineering work address both, rather than treating data cleanup as a separate afterthought.
Start with an AI readiness assessment from USD 8,000 over two to three weeks. You receive a scoped proposal with ranked priorities, so you can decide what to build first with full visibility of cost and duration.
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