AI enterprise solutions that move large organisations from pilots to production
Paloren delivers AI enterprise solutions worldwide: strategy, company brain, agents, automation, CRM, governance and training from co-founder Aaron Agius.
Executives and operations leaders in large companies implementing AI across departments
Paloren designs and delivers AI enterprise solutions for companies worldwide, covering strategy, implementation, automation and training. Paloren combines implementation, workflow design and practical team training. First projects run USD 25k-100k over 2-10 weeks.
For Paloren, AI enterprise solutions are connected systems that carry real operational load across a large organisation.
The phrase covers the full service stack: AI strategy, the company brain, AI agents, workflow automation and integrations, CRM implementation with AI, AI voice agents and receptionists, custom apps, AI governance, the AI readiness assessment and team AI training.
What separates an enterprise solution from a collection of tools is the way the parts reinforce each other. Strategy decides where AI earns its place. The company brain organises knowledge so agents and people draw on the same base.
Automation and integrations move work between systems without manual handoffs. Governance keeps usage controlled, and training makes adoption stick. Paloren delivers this stack for companies worldwide, with implementation as the pillar that turns decisions into running systems.
The work, made concrete
A connected stack, not a set of disconnected pilots
Ten services spanning assessment, strategy, build, governance and training
Most stalled enterprise AI programmes share the same pattern. Ideas arrive faster than foundations. Knowledge sits in scattered documents and inboxes, so any tool built on top of it produces shallow answers.
Systems do not talk to each other, so every pilot ends at a manual export. Ownership is unclear, so nobody signs off on how a model should behave or who reviews its output.
And training arrives last, if at all, so staff quietly return to old habits. Paloren addresses these blockers in a fixed order. The readiness assessment exposes the true state of systems, data and workflows before anyone commits to a build.
Strategy then sets priorities and governance direction, so each project has an owner and a purpose. Implementation follows with the company brain, agents, automation and CRM work, each scoped with timelines measured in weeks.
Governance and training run through delivery rather than after it. The result is momentum that survives contact with reality: fewer initiatives, each one integrated, owned and actually used by the departments it was built for.
| Service | What it delivers | Typical range and timeline |
|---|---|---|
| AI readiness assessment | Baseline of systems, data and workflows with a prioritised use case map | From USD 8k over 2-3 weeks |
| AI strategy | Roadmap, priorities and governance direction for enterprise adoption | USD 12k-25k over 3-4 weeks |
| Company brain | Central knowledge layer connecting documents, data and workflows | USD 60k-150k over 8-12 weeks |
| AI agents | Task-specific agents working across enterprise systems | USD 40k-90k over 6-10 weeks |
| Workflow automation and integrations | Automated processes across core platforms | USD 15k-60k over 3-8 weeks |
| CRM implementation with AI | CRM configured with AI built into sales and service motions | USD 20k-80k over 4-10 weeks |
| AI voice agents and receptionists | Voice systems handling inbound calls and routing | USD 25k-60k over 4-8 weeks |
| Custom apps | Purpose-built applications around enterprise workflows | From USD 40k |
| AI governance | Policies, access rules and review structures for enterprise AI | Scoped within strategy or as a focused programme |
| Team AI training | Role-based training so staff operate new systems confidently | Scoped to team size and format |
Ranges reflect typical first engagements; final scope is confirmed after a readiness assessment.
Source: Paloren published service ranges
| Business area | Typical AI application | Matching Paloren service |
|---|---|---|
| Sales | Call analysis, record updates and follow-up drafting inside the CRM | CRM implementation with AI |
| Marketing | Content systems and reporting built on organised knowledge | Company brain |
| Customer service | Chat and voice handling routine enquiries with human escalation | AI voice agents and receptionists |
| Operations | Automation across approvals, handoffs and platform integrations | Workflow automation and integrations |
| Knowledge management | One searchable layer for documents, policies and data | Company brain |
| Risk and compliance | Usage policies, access controls and review points | AI governance |
| Front desk | Voice reception that routes calls and captures context | AI voice agents and receptionists |
Typical landing points for AI in large organisations, each mapped to a Paloren service.
Source: Paloren published service ranges
| Engagement | Purpose | Structure |
|---|---|---|
| Readiness assessment | Establish where AI should land first and what needs fixing | From USD 8k over 2-3 weeks |
| First project | Prove value with a scoped build such as agents, automation or CRM | USD 25k-100k over 2-10 weeks |
| Company brain programme | Build the enterprise knowledge layer | USD 60k-150k over 8-12 weeks |
| Ongoing support | Maintain, extend and train as systems evolve | From USD 2,500 per month for 10 hours |
First projects sit between USD 25k-100k over 2-10 weeks; ongoing support starts at USD 2,500 per month for 10 hours.
Source: Paloren published service ranges
The work, made concrete
Scattered knowledge and disconnected systems break most pilots
Unclear ownership leaves no one accountable for AI behaviour
Readiness first, then strategy, then builds with owners attached
Paloren offers ten services that map onto the enterprise AI lifecycle. The AI readiness assessment comes first, from USD 8k over 2-3 weeks, giving leadership an evidence-based view of where to invest.
AI strategy, USD 12k-25k over 3-4 weeks, converts that view into a roadmap. The company brain, USD 60k-150k over 8-12 weeks, builds the central knowledge layer everything else depends on.
AI agents, USD 40k-90k over 6-10 weeks, take on defined tasks end to end. Workflow automation and integrations, USD 15k-60k over 3-8 weeks, connect systems so work flows without manual transfers.
CRM implementation with AI, USD 20k-80k over 4-10 weeks, embeds intelligence into sales and service. AI voice agents and receptionists, USD 25k-60k over 4-8 weeks, handle inbound calls.
Custom apps start from USD 40k where off-the-shelf tools fall short. AI governance and team AI training complete the set, keeping usage controlled and people capable. Enterprises rarely need all ten at once; the assessment and strategy determine the right sequence.
The work, made concrete
Ten services covering assessment through ongoing support
Each build scoped with a published range and timeline
Sequence set by the assessment, not by a fixed bundle
The company brain is Paloren's answer to enterprise knowledge that lives everywhere and helps nowhere. It pulls documents, data and workflow context into one organised layer, then serves that layer to people, AI agents and automations alike.
Ask a question and the answer reflects your actual policies and numbers. Point an agent at it and the agent acts on current information instead of a stale copy.
That origin matters for enterprises because the same pattern repeats at larger size: reporting that contradicts the CRM, service teams missing call context, content built on outdated positioning.
A company brain resolves those fractures before agents and automations are layered on top. Paloren delivers it over 8-12 weeks, typically between USD 60k-150k, and treats it as the foundation phase of enterprise implementation rather than an optional add-on.
The work, made concrete
One organised layer serving people, agents and automations
Delivered in 8-12 weeks, typically USD 60k-150k
Agents and automation are where enterprise AI stops describing work and starts doing it. Paloren builds AI agents, USD 40k-90k over 6-10 weeks, to complete defined tasks end to end: working through queues, drafting responses, updating records and escalating the cases that need human judgement.
Workflow automation and integrations, USD 15k-60k over 3-8 weeks, handle the connective tissue, moving information between CRM, reporting and operational platforms so no one re-keys data between systems.
AI voice agents and receptionists, USD 25k-60k over 4-8 weeks, extend this to the phone, answering inbound calls, routing them and capturing context before a person picks up.
At enterprise scale the mechanics apply with higher stakes, which is why every build runs under the governance framework and lands with role-based training. Departments keep their judgement; the repetitive layer underneath it gets handed to systems that do not tire.
The work, made concrete
Agents complete defined tasks end to end with escalation paths
Integrations move data between CRM, reporting and operations
Voice agents answer, route and capture context on inbound calls
Enterprise AI fails quietly when governance is bolted on late or training is skipped entirely. Paloren treats both as deliverables in their own right.
AI governance sets usage policies, access rules and review points, documented so leaders can see how systems behave, where humans stay in the loop and what happens when something drifts.
It can run inside a wider programme or as a focused engagement alongside strategy, whichever fits the organisation's stage. Adoption is handled through team AI training, which covers the specific tools each role touches: the company brain, agents, automation and the CRM.
Sessions are practical, so staff leave able to operate, question and extend what was built. This matters because enterprise systems live or die by daily use; a technically sound platform that people avoid is a failed investment.
Delivery therefore closes every build with documented governance and trained operators, and ongoing support from USD 2,500 per month for 10 hours keeps both current as systems, teams and requirements evolve.
The work, made concrete
Usage policies, access rules and review points, documented
Role-based training on the company brain, agents, automation and CRM
Support from USD 2,500 per month for 10 hours keeps systems current
Paloren combines implementation, workflow design and practical team training. This combination shapes how engagements run: growth-system thinking sets the direction, large-organisation experience sets the guardrails, and delivery teams execute in weeks rather than quarters.
Enterprises work with a leadership team that has both built systems and operated inside the environments those systems must survive.
The work, made concrete
Co-founded by Aaron Agius and Alex Agius
Aaron brings 20 years of growth systems and co-authored Faster, Smarter, Louder
Team experience spans IBM, Ford, LG, Unilever, Jaguar and Chelsea FC
Engagements follow a deliberate arc. It opens with a readiness assessment, from USD 8k over 2-3 weeks, which maps systems, data, workflows and gaps, then ranks where AI should land first.
Strategy, USD 12k-25k over 3-4 weeks, turns those findings into a roadmap with owners, budgets and governance direction.
Build phases then follow in sequence: the company brain over 8-12 weeks where a knowledge layer is needed, agents over 6-10 weeks for task automation, workflow automation over 3-8 weeks for integrations, CRM implementation over 4-10 weeks, voice agents over 4-8 weeks and custom apps from USD 40k.
Most enterprises start with one scoped first project, USD 25k-100k over 2-10 weeks, prove the value, then extend. Governance and training run alongside the builds rather than after them, so adoption is underway by launch.
Once systems are live, support from USD 2,500 per month for 10 hours covers maintenance, extensions and further training. Every phase has defined deliverables, so leadership always knows what has shipped and what comes next.
The work, made concrete
Assessment and strategy before any build is committed
Scoped first projects of USD 25k-100k over 2-10 weeks
Defined deliverables at every phase, then ongoing support
Starting is deliberately small relative to the scale of the ambition. The entry point is the AI readiness assessment, from USD 8k over 2-3 weeks. It requires no prior AI programme, no internal data science team and no reorganisation; it needs access to the systems and people who know how work actually flows.
The assessment outputs a prioritised use case map and a clear statement of what must be fixed before builds begin. From there, most enterprises follow with an AI strategy at USD 12k-25k over 3-4 weeks to sequence the roadmap, then commit to a first project within the USD 25k-100k band over 2-10 weeks.
Delivery is remote and serves companies worldwide, so location never constrains participation. Leadership gets a single point of contact, clear visibility and defined deliverables rather than open-ended discovery.
If the assessment reveals that a different sequence serves better, the roadmap says so before major budget is spent. The honest path into enterprise AI is short, evidence-based and reversible at every step.
The work, made concrete
Start with the readiness assessment, from USD 8k over 2-3 weeks
Remote delivery serving companies worldwide
Single point of contact and defined deliverables throughout
Map systems, data and workflows in 2-3 weeks, from USD 8k, and rank the use cases where AI will pay first.
Convert assessment findings into a 3-4 week strategy that fixes priorities, budgets, owners and governance direction.
Stand up the central knowledge layer over 8-12 weeks so agents, automations and teams share one source of truth.
Roll out task-specific agents and workflow integrations in controlled waves, from voice reception to CRM updates.
Run role-based sessions on each system so staff operate, question and extend what has been built.
Keep systems current with support from USD 2,500 per month for 10 hours, covering maintenance and extensions.
| Service | What it delivers | Typical range and timeline |
|---|---|---|
| AI readiness assessment | Baseline of systems, data and workflows with a prioritised use case map | From USD 8k over 2-3 weeks |
| AI strategy | Roadmap, priorities and governance direction for enterprise adoption | USD 12k-25k over 3-4 weeks |
| Company brain | Central knowledge layer connecting documents, data and workflows | USD 60k-150k over 8-12 weeks |
| AI agents | Task-specific agents working across enterprise systems | USD 40k-90k over 6-10 weeks |
| Workflow automation and integrations | Automated processes across core platforms | USD 15k-60k over 3-8 weeks |
| CRM implementation with AI | CRM configured with AI built into sales and service motions | USD 20k-80k over 4-10 weeks |
| AI voice agents and receptionists | Voice systems handling inbound calls and routing | USD 25k-60k over 4-8 weeks |
| Custom apps | Purpose-built applications around enterprise workflows | From USD 40k |
| AI governance | Policies, access rules and review structures for enterprise AI | Scoped within strategy or as a focused programme |
| Team AI training | Role-based training so staff operate new systems confidently | Scoped to team size and format |
Ranges reflect typical first engagements; final scope is confirmed after a readiness assessment.
Paloren published service ranges
| Business area | Typical AI application | Matching Paloren service |
|---|---|---|
| Sales | Call analysis, record updates and follow-up drafting inside the CRM | CRM implementation with AI |
| Marketing | Content systems and reporting built on organised knowledge | Company brain |
| Customer service | Chat and voice handling routine enquiries with human escalation | AI voice agents and receptionists |
| Operations | Automation across approvals, handoffs and platform integrations | Workflow automation and integrations |
| Knowledge management | One searchable layer for documents, policies and data | Company brain |
| Risk and compliance | Usage policies, access controls and review points | AI governance |
| Front desk | Voice reception that routes calls and captures context | AI voice agents and receptionists |
Typical landing points for AI in large organisations, each mapped to a Paloren service.
| Engagement | Purpose | Structure |
|---|---|---|
| Readiness assessment | Establish where AI should land first and what needs fixing | From USD 8k over 2-3 weeks |
| First project | Prove value with a scoped build such as agents, automation or CRM | USD 25k-100k over 2-10 weeks |
| Company brain programme | Build the enterprise knowledge layer | USD 60k-150k over 8-12 weeks |
| Ongoing support | Maintain, extend and train as systems evolve | From USD 2,500 per month for 10 hours |
First projects sit between USD 25k-100k over 2-10 weeks; ongoing support starts at USD 2,500 per month for 10 hours.
Readiness report with a prioritised AI use case map
Enterprise AI strategy and implementation roadmap
Company brain connecting documents, data and workflows
AI agents handling defined tasks end to end
Automated workflows and integrations across core platforms
CRM implemented with AI built into sales and service
Governance framework with documented policies and review points
Role-based training plus an ongoing support option
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.
S4 applies to the full enterprise AI stack: strategy, company brain, agents, automation, CRM, governance and training. Each stage is scoped in weeks and owned by a named leader.
| Step | Stage | What it changes |
|---|---|---|
| 01 | Signal | Run the AI readiness assessment across departments: scattered documents, disconnected systems, manual exports, stalled pilots and which workflows carry real operational load. |
| 02 | Synthesis | Set strategy priorities with a named owner per project, define how the company brain organises knowledge, and fix governance rules for model behaviour and output review. |
| 03 | System | Build the company brain, agents, workflow automations and CRM implementation with AI; test integrations so no pilot ends at a manual handoff between systems. |
| 04 | Scale | Pair rollout with AI training so adoption sticks, track usage by department, and extend one integrated workflow at a time rather than piling up new initiatives. |
Any connected system that helps a large organisation run on AI rather than experiment with it. That covers strategy, the company brain, AI agents, workflow automation and integrations, CRM implementation with AI, voice agents and receptionists, custom apps, governance and training.
The common thread is production use: systems that handle real work across departments, not isolated demos.
Timelines follow scope. A readiness assessment runs 2-3 weeks and AI strategy takes 3-4 weeks. Builds vary: automation runs 3-8 weeks, agents 6-10 weeks, CRM implementation 4-10 weeks and a company brain 8-12 weeks.
Most first projects land between USD 25k-100k over 2-10 weeks, with milestones agreed before work starts.
Budgets follow the engagement. Readiness starts from USD 8k over 2-3 weeks. Strategy sits at USD 12k-25k over 3-4 weeks. First projects range from USD 25k-100k over 2-10 weeks, while larger programmes such as the company brain reach USD 60k-150k over 8-12 weeks. Ongoing support starts at USD 2,500 per month for 10 hours.
Yes. Implementation runs alongside internal teams rather than around them. Paloren handles strategy, architecture and builds while your engineers keep ownership of infrastructure and access.
Integration work covers CRM, reporting and core platforms, and governance is documented so internal standards carry through. Training then transfers day-to-day operation to your people.
Large organisations rarely lack AI ideas; they lack a clear picture of which ideas will pay off. The assessment maps systems, data and workflows, flags gaps and ranks use cases by impact and effort.
The result is a shortlist you can commit budget to, plus a view of what governance and training will be needed before builds begin.
The company brain is a central knowledge layer that connects documents, data and workflows so people and AI agents work from one source. At enterprise scale it removes the guesswork from reporting, service and content, because every system draws on the same organised base. Paloren builds it over 8-12 weeks, typically between USD 60k-150k.
Yes. Governance is part of the service list: usage policies, access rules, review points and documentation that show how AI systems make decisions and where humans stay in the loop.
It can be built into a wider programme or run as a focused piece of work alongside strategy, so adoption never outruns control.
Training is a core Paloren service, not an afterthought. Sessions are role-based, covering the tools each team touches: the company brain, agents, automation and CRM. The aim is internal capability, so your people operate, question and extend the systems without waiting on outside help. Ongoing support can back this up from USD 2,500 per month.
Worldwide. Delivery is remote by default, which suits enterprises spread across regions and time zones. There is no requirement to be near a specific location: assessments, builds, training and support all run online with structured checkpoints.
Enterprises in any country can start with a readiness assessment and move into implementation from there.
Aaron Agius, co-founder of Paloren, leads the direction of enterprise engagements. Paloren combines implementation, workflow design and practical team training.
Where should AI land first in your enterprise?
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