Business analysis services that prepare organisations for AI
Paloren provides business analysis services that map processes, data and systems, then rank AI opportunities so teams invest where returns are clearest.
Leaders and operations teams preparing to invest in AI and automation
Paloren provides business analysis services that map processes, data and systems before AI investment. Co-founded by Aaron Agius, an AI implementation consultant, alongside Alex Agius, Paloren turns analysis into a ranked set of AI opportunities and a practical roadmap.
Teams worldwide use these engagements to decide where agents, automation or a company brain will earn their keep first.
Business analysis services at Paloren cover the full operating picture of an organisation: how work flows through teams, where data is created and stored, which systems hold which truths, and where decisions stall or get duplicated.
The work sits under the AI strategy pillar because it produces the evidence that strategy needs. Paloren treats each analysis business service engagement as groundwork rather than paperwork, so every hour spent mapping converts directly into ranked opportunities.
Coverage typically includes core processes and their handoffs, reporting and measurement, customer-facing workflows, back-office administration, integration points between tools, and the governance questions that surface when automation enters a process.
Because Paloren serves businesses worldwide, engagements are structured to run remotely with teams spread across countries and time zones. Nothing is taken from slide decks alone; claims are checked against what systems and people actually do each week.
The result is a shared, written understanding of how the business operates, which becomes the baseline for every AI decision that follows.
The work, made concrete
Process, data and system mapping across the whole operating model
Handoffs, reporting and decision points documented as they really run
Remote delivery for teams spread across countries and time zones
AI projects fail most often for reasons that have nothing to do with the technology. A process nobody has documented, data that lives in five places with five owners, or a decision that quietly depends on one person's memory will break any agent or automation placed on top of it.
Analysis finds these conditions first. Skipping analysis means buying tools before knowing the job. It leads to automating a broken process, building an agent on unreliable data, or committing a large first project, typically USD 25,000 to 100,000 over 2 to 10 weeks, to the wrong target.
A short analytical phase protects that investment by pointing effort at the workflows where AI will actually hold. It is cheaper to discover a blocked path in a workshop than after a build contract is signed.
| Analysis Area | What Is Examined | Output |
|---|---|---|
| Processes and workflows | Steps, handoffs, inputs, outputs and cycle time | Current state process map |
| Data | Sources, storage, access, quality and decision fields | Data landscape summary |
| Systems and integrations | Tools in place, connections between them, manual gaps | System and integration review |
| People and decisions | Ownership, approval rights, exceptions and workarounds | Decision and ownership notes |
| Governance and risk | Data handling, accountability and control needs | Risk and governance register |
| AI opportunities | Candidate use cases scored for value and feasibility | Ranked opportunity register |
Each area is examined and documented during a Paloren analysis engagement.
Source: Paloren published service ranges
| Service | Investment Range | Typical Duration |
|---|---|---|
| AI readiness assessment | From USD 8,000 | 2 to 3 weeks |
| AI strategy | USD 12,000 to 25,000 | 3 to 4 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 |
| AI agents | USD 40,000 to 90,000 | 6 to 10 weeks |
| Company brain | USD 60,000 to 150,000 | 8 to 12 weeks |
| Custom apps | From USD 40,000 | Defined at scoping |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
Investment ranges and durations for the services analysis most often feeds into.
Source: Paloren published service ranges
The work, made concrete
Unclear processes and unowned data break AI before it starts
Analysis protects larger build budgets from targeting the wrong work
Examination follows a consistent structure so findings can be compared and ranked. Processes come first: each significant workflow is walked from trigger to outcome, capturing inputs, steps, handoffs, outputs and the time each stage consumes.
Data comes next: where records originate, where they are stored, who can access them, how clean they are and which fields drive decisions. Systems follow: the tools in place, the integrations between them, the gaps where people copy information manually, and the reporting that leadership relies on.
People and decisions are examined too, because approval rights, exceptions and informal workarounds often determine whether automation can succeed. Finally, governance and risk are reviewed, covering data handling, accountability and the controls needed before AI touches a process.
The breadth matters: a gap in any one layer, such as unreachable data or an undefined owner, can disqualify an otherwise attractive opportunity. This structure keeps the engagement focused on evidence rather than opinion, and each layer is documented in writing so findings stay useful long after the engagement closes.
The work, made concrete
Workflow walkthroughs capturing inputs, steps, handoffs and cycle time
Data origin, storage, access and quality assessed layer by layer
Governance and risk reviewed before AI touches any process
Analysis and strategy are sequential at Paloren. Analysis produces the factual base: what the business does, where the friction sits, what the data supports and which systems can connect.
Strategy then turns that base into choices: which opportunities to pursue, in what order, with which Paloren services, and what each phase should return. Without the analytical base, strategy becomes guesswork dressed as a roadmap.
With it, every recommendation can be traced to an observed process or a measured constraint. The connection also runs through Paloren's service structure. The AI readiness assessment, from USD 8,000 over 2 to 3 weeks, gives a fast read on where the organisation stands.
The AI strategy engagement, USD 12,000 to 25,000 over 3 to 4 weeks, builds the full plan on top of analytical findings. Deeper analysis work sits inside both.
Teams that already hold current process maps often move through strategy faster, because the discovery burden is lower and debate shifts from arguing about facts to making decisions.
The work, made concrete
Analysis supplies facts; strategy converts facts into sequenced choices
Readiness assessment from USD 8,000 over 2 to 3 weeks
Strategy engagement USD 12,000 to 25,000 over 3 to 4 weeks
The people doing the analysis shape its quality, so Paloren staffs engagements with senior practitioners rather than rotating juniors. Alex Agius co-founded Paloren and leads the technical side of delivery.
Paloren combines implementation, workflow design and practical team training. That background matters during interviews: questions come from experience with how enterprises actually run, so stakeholders are asked about the exceptions, workarounds and system constraints that generic questionnaires miss.
The same senior team that scopes the engagement stays involved through findings and roadmap, keeping continuity from first conversation to final recommendation. No part of the work is handed to unnamed staff.
The work, made concrete
Aaron Agius brings 20 years building marketing, data and growth systems
Alex Agius co-founded Paloren and leads technical delivery
Practitioner experience inside IBM, Ford, LG, Unilever, Jaguar and Chelsea FC
Risk in AI projects concentrates in a few predictable places: data that cannot support the task, processes that vary between teams, systems that will not integrate, and decisions nobody has authorised an agent to make.
Analysis surfaces each of these before money is committed to a build. An opportunity that looks valuable in a pitch can be ruled out early if the data behind it is fragmented or access is restricted, saving the cost of a failed implementation.
Analysis also rightsizes ambition. Some workflows justify AI agents, priced at USD 40,000 to 90,000 over 6 to 10 weeks; others need only workflow automation at USD 15,000 to 60,000 over 3 to 8 weeks; some need no build at all, just a clarified process.
Matching spend to evidence is how risk falls. Governance findings feed the AI governance service, so controls are designed alongside opportunities rather than bolted on after deployment, when changes cost far more.
Every risk noted during analysis carries a suggested response in the final report.
The work, made concrete
Fragmented data, variable processes and blocked integrations found early
Spend matched to evidence, from simple automation to full agents
Governance controls designed alongside opportunities, not after deployment
Cost depends on depth. The fastest route is the AI readiness assessment, from USD 8,000 over 2 to 3 weeks, which delivers a structured read of processes, data, systems and AI readiness.
Where the questions are broader, analysis sits inside the AI strategy engagement at USD 12,000 to 25,000 over 3 to 4 weeks. For organisations preparing a significant build, fuller analytical work folds into the first project, which ranges from USD 25,000 to 100,000 over 2 to 10 weeks depending on scope.
These figures cover defined engagements with named deliverables, not open-ended day rates. Optional ongoing support starts at USD 2,500 per month for 10 hours, useful after analysis when teams want help interpreting findings or preparing internal approvals.
Scope, the number of workflows examined and stakeholder availability drive the final figure, so Paloren confirms pricing after a short scoping conversation instead of quoting before scope is known. Every quote lists what will be examined and what will be delivered.
The work, made concrete
Readiness assessment from USD 8,000 over 2 to 3 weeks
Strategy engagement USD 12,000 to 25,000 over 3 to 4 weeks
Optional support from USD 2,500 per month for 10 hours
Analysis ends with a decision point, not a sales pitch. Teams receive the findings, the ranked opportunity register and the roadmap, then choose their pace. Some take the documents internally and plan budgets across the following year.
Others move straight into implementation with Paloren, and the roadmap tells them which service fits first. A company brain, USD 60,000 to 150,000 over 8 to 12 weeks, suits organisations that need a central knowledge layer.
AI agents, USD 40,000 to 90,000 over 6 to 10 weeks, suit teams ready to delegate defined tasks. CRM implementation with AI, USD 20,000 to 80,000 over 4 to 10 weeks, fits sales and service functions that need cleaner pipelines.
Chatbots run USD 20,000 to 50,000 over 4 to 8 weeks, voice agents USD 25,000 to 60,000 over 4 to 8 weeks, and custom apps start from USD 40,000. Team AI training often runs alongside, so people are ready for the systems the analysis recommended.
The work, made concrete
Findings, opportunity register and roadmap handed over for decisions
Roadmap maps each opportunity to a specific Paloren service
Team AI training prepares people for recommended systems
Engagement starts with a conversation about goals, current systems and the decisions the analysis should support.
Paloren serves businesses worldwide, and engagements are built for distributed teams: interviews and workshops run remotely, sessions are scheduled across time zones, and documentation is shared in writing so people in different countries work from the same record.
Preparation is light. Teams bring process owners, a system or data lead and an executive sponsor; Paloren brings the structure, the questioning and the documentation. Work proceeds in stages, so early findings can redirect attention before the engagement closes.
Because Paloren works at country level without anchoring engagements to physical locations, geography never limits who can take part; what matters is access to the people who run the processes being examined.
The scoping conversation carries no obligation and ends with a written proposal covering scope, duration, deliverables and the investment range that applies, so leadership can approve with full information.
The work, made concrete
Remote interviews and workshops across countries and time zones
Light preparation: process owners, a data lead, an executive sponsor
Written proposal covering scope, duration, deliverables and investment range
A structured session captures goals, constraints, systems in use and the decisions the analysis must support.
Workflows, handoffs, data sources and reporting are documented as they actually operate, not as described on paper.
Existing tools, connections and manual gaps are assessed to establish what AI can attach to safely.
Use cases across agents, automation, CRM intelligence and a company brain are scored for value, feasibility and risk.
A written report presents ranked opportunities, risks and a sequenced plan leadership can approve.
| Analysis Area | What Is Examined | Output |
|---|---|---|
| Processes and workflows | Steps, handoffs, inputs, outputs and cycle time | Current state process map |
| Data | Sources, storage, access, quality and decision fields | Data landscape summary |
| Systems and integrations | Tools in place, connections between them, manual gaps | System and integration review |
| People and decisions | Ownership, approval rights, exceptions and workarounds | Decision and ownership notes |
| Governance and risk | Data handling, accountability and control needs | Risk and governance register |
| AI opportunities | Candidate use cases scored for value and feasibility | Ranked opportunity register |
Each area is examined and documented during a Paloren analysis engagement.
Paloren published service ranges
| Service | Investment Range | Typical Duration |
|---|---|---|
| AI readiness assessment | From USD 8,000 | 2 to 3 weeks |
| AI strategy | USD 12,000 to 25,000 | 3 to 4 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 |
| AI agents | USD 40,000 to 90,000 | 6 to 10 weeks |
| Company brain | USD 60,000 to 150,000 | 8 to 12 weeks |
| Custom apps | From USD 40,000 | Defined at scoping |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
Investment ranges and durations for the services analysis most often feeds into.
Current state map of processes, data flows and systems
Ranked AI opportunity register with feasibility and risk notes
System and integration review highlighting manual gaps
Prioritised roadmap linking each opportunity to a Paloren service
Written summary prepared for leadership decisions
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.
Business analysis services examine how an organisation actually operates: its processes, data, systems, decisions and controls. Paloren delivers this work as the foundation for AI strategy and implementation, documenting each workflow in full, assessing data quality and access, and producing a ranked register of AI opportunities.
The output gives leadership evidence for deciding where automation, agents or a company brain should be built first.
An AI readiness assessment is a focused engagement, from USD 8,000 over 2 to 3 weeks, that measures how prepared the organisation is for AI across processes, data, systems and skills.
Broader business analysis goes further, walking specific workflows through every step and building the opportunity register that strategy and implementation draw on. Many engagements combine both, with assessment providing the snapshot and analysis providing the depth behind it.
Yes. Paloren serves businesses worldwide and structures engagements for distributed teams. Interviews, workshops and reviews run remotely, sessions are scheduled across time zones, and all findings are documented in writing so people in every location work from the same record.
What matters is access to the people who run the processes being examined, not where those people sit.
Duration follows depth. An AI readiness assessment runs 2 to 3 weeks. Analysis delivered inside an AI strategy engagement fits within 3 to 4 weeks.
Where analysis forms the first stage of a larger programme, the combined first project ranges from 2 to 10 weeks depending on how many workflows, systems and decision areas are examined.
Paloren confirms the timeline in the written proposal before work starts.
No. Analysis stands on its own, and many teams use the findings, opportunity register and roadmap to plan internally before committing to any build. If you do proceed, the roadmap already sequences which Paloren service fits first, so implementation starts from shared evidence rather than another discovery phase. Either way, the documents belong to you.
Three roles usually suffice: the people who own the processes being examined, a system or data lead who can explain where information lives, and an executive sponsor who can confirm priorities and approve findings.
Time commitments are modest, mostly scheduled interviews and a findings session. Paloren handles structure, questioning and documentation, so your team's burden stays focused on sharing how work really runs.
Every opportunity in the final register maps to a specific Paloren service. Tasks that repeat with clear rules point toward workflow automation or AI agents. Fragmented knowledge across teams points toward a company brain.
Sales and service workflows point toward CRM implementation with AI, while phone-heavy processes suit voice agents. The roadmap then sequences these builds so each one lands on prepared processes and clean data.
Standalone analytical work is most commonly delivered through the AI readiness assessment, from USD 8,000 over 2 to 3 weeks, or through the AI strategy engagement at USD 12,000 to 25,000 over 3 to 4 weeks where the scope is wider.
If ongoing help is wanted after delivery, support starts at USD 2,500 per month for 10 hours. Final pricing is confirmed in a written proposal once scope is agreed.
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