Agentic AI development services that turn workflows into autonomous systems
Paloren builds agentic AI systems, from strategy and design to deployed autonomous agents, automating workflows for companies worldwide.
Operations, technology and growth leaders who want autonomous AI agents handling real work
Paloren delivers agentic AI development services that design, build and run autonomous agents for companies worldwide. Agent engagements typically range from USD 40k to 90k across six to ten weeks.
Agentic AI development services cover the design, build and operation of software agents that pursue goals rather than follow fixed scripts. A traditional automation waits for a trigger and repeats the same steps.
An agent receives an objective, plans a sequence of actions, calls the tools it needs, checks its own output and adjusts when something changes. Paloren provides these services to companies worldwide, taking agent projects from first concept through architecture, development, integration and governance.
The work sits at the intersection of strategy and engineering: someone has to decide which decisions a machine may make, and someone has to build the plumbing that lets it act. Paloren handles both.
The work, made concrete
Agents pursue goals and adapt rather than repeating fixed scripts
Every build combines strategy, engineering and governance
Paloren was co-founded by Aaron Agius and Alex Agius, and that pairing shapes how every agent project runs. Alex Agius co-founded Paloren, and together the founders steer agent projects from first assessment through to deployment and support.
Paloren combines implementation, workflow design and practical team training. The people who assess your readiness and shape your strategy stay involved through development and beyond, because agents change how a business runs and accountability should not pass to whoever happens to be writing the code that week.
The work, made concrete
Co-founded by Aaron Agius and Alex Agius
Team experience includes IBM, Ford, LG, Unilever, Jaguar and Chelsea FC
| Service | Typical range (USD) | Typical duration |
|---|---|---|
| AI agents | 40k-90k | 6-10 weeks |
| Workflow automation and integrations | 15k-60k | 3-8 weeks |
| AI voice agents and receptionists | 25k-60k | 4-8 weeks |
| AI chatbots | 20k-50k | 4-8 weeks |
| CRM implementation with AI | 20k-80k | 4-10 weeks |
| Company brain | 60k-150k | 8-12 weeks |
| Custom apps | From 40k | Scoped during planning |
A first project typically falls between USD 25k and 100k over 2 to 10 weeks.
Source: Paloren published service ranges
| Factor | Effect on the build |
|---|---|
| Number of connected systems | Each CRM, tool or data source adds design, testing and governance work |
| Level of autonomy | Agents that act without approval need stronger guardrails and monitoring |
| Data readiness | Clean, connected data shortens development, while fragmented data extends it |
| Approval and compliance needs | Consequential decisions require audit trails and human checkpoints |
| Scope of the first release | A focused first agent ships faster than a broad multi-agent program |
Only the published ranges above are fixed figures; everything else is scoped per engagement.
Source: Paloren published service ranges
Agent builds at Paloren fall into several families, each mapped to a service line. CRM agents keep records current, route follow-ups and surface the next best action through CRM implementation with AI.
Voice agents and AI receptionists answer calls, qualify conversations and hand off to people when judgement is required. Workflow agents connect tools that never spoke to each other, moving work between departments without manual re-entry.
Knowledge agents, often delivered as a company brain, give staff one place to ask questions and receive answers grounded in your own documents and data. Most engagements combine two or three families, because an agent that writes a report is more useful when a second routes the follow-up and a third keeps the CRM honest.
Paloren scopes the mix during strategy so the first release proves the pattern before the program expands.
The work, made concrete
Reporting, CRM, voice, content, workflow and knowledge agent families
Most builds combine several agent families into one coordinated system
The mix is scoped during strategy so the first release proves the pattern
Development follows a sequence that starts before any code is written. An AI readiness assessment, from USD 8k over two to three weeks, maps your systems, data, risks and the workflows where agents could act.
AI strategy, USD 12k to 25k over three to four weeks, turns that map into a prioritised plan naming which agents to build first and what each may be allowed to do.
Design then defines the agent loop: the goal, the tools it may call, the data it may read, the actions requiring human approval and the audit trail recording every decision.
Build and integration follow, connecting the agent to your CRM, communication channels and data sources, then testing against real scenarios rather than toy examples. Governance wraps the whole system, setting guardrails, monitoring and escalation paths before anything reaches production.
A typical agent engagement runs USD 40k to 90k over six to ten weeks, with narrower automation work from USD 15k to 60k over three to eight weeks. Nothing ships without the checks that let your team trust it.
The work, made concrete
Readiness assessment first, strategy second, build third
Agent design fixes tools, data access and human approval points up front
Typical agent engagements run USD 40k to 90k over six to ten weeks
Costs depend on scope, and Paloren publishes its ranges so planning starts with real numbers. A first project typically sits between USD 25k and 100k over two to ten weeks.
A dedicated agent build runs USD 40k to 90k across six to ten weeks. Workflow automation and integrations land between USD 15k and 60k over three to eight weeks, while AI voice agents and receptionists run USD 25k to 60k over four to eight weeks.
Chatbot deployments sit at USD 20k to 50k over four to eight weeks, custom apps start at USD 40k, and a company brain, the knowledge layer many agents draw on, ranges from USD 60k to 150k over eight to twelve weeks.
Ongoing support starts at USD 2,500 per month for ten hours. Two levers move a project inside these ranges: how many systems the agent must reach and how much autonomy it is granted.
An agent that drafts a summary for human review costs less to build safely than one that acts without asking.
The work, made concrete
First projects typically fall between USD 25k and 100k over 2 to 10 weeks
Agent builds run USD 40k to 90k over six to ten weeks
Integration depth and autonomy level are the main cost levers
Timelines follow the same logic as costs. Expect two to three weeks for a readiness assessment and three to four weeks for strategy, so a deliberate program spends its first month understanding the business rather than building blind.
A focused agent then takes six to ten weeks from design to production. Narrower automation work finishes in three to eight weeks, voice agents and receptionists in four to eight, chatbots on a similar clock and CRM implementations with AI in four to ten.
A company brain takes eight to twelve weeks because it touches many systems at once. Voice work can proceed in parallel once call flows are agreed, which shortens the calendar without shortening the testing.
Sequencing matters more than speed: an agent built on unassessed foundations often needs rework, while one built after a short assessment tends to hold. Paloren plans each engagement so the early weeks produce decisions, not just documents, and the build phase starts with the highest value workflow already agreed.
The work, made concrete
Assessment and strategy take five to seven weeks combined
A focused agent reaches production in six to ten weeks
Company brain builds take eight to twelve weeks across many systems
An agent is only useful if it can act where work actually happens, so integration is a core part of every build, not an afterthought. Paloren connects agents to CRM platforms so records update themselves and follow-ups never wait for someone to type them.
Agents read from and write to the tools your teams already use, moving information between systems that were never designed to talk. Voice agents plug into phone lines so reception and call handling become automated without changing your numbers.
Where no suitable tool exists, Paloren builds custom apps, starting at USD 40k, that give agents and people a shared interface. For organisations that want a knowledge layer, a company brain becomes the memory agents draw on, so answers reflect your documents and data rather than generic training material.
Every connection is designed with permissions in mind: the agent sees what it needs, records what it does and escalates to a person when a step falls outside its mandate.
The work, made concrete
Agents connect to CRM, communication tools and data sources
Custom apps from USD 40k fill gaps no existing tool covers
Permissions, logging and escalation are designed into every connection
Autonomy without control is a liability, so governance is a service line in its own right. Every agent Paloren ships carries guardrails that define what it may do, what it must ask permission for and what it must never touch.
Actions are logged, so any decision an agent made can be traced after the fact. Human approval points sit in front of consequential steps, such as sending external communications or changing records at scale.
Monitoring watches for drift, errors and unusual patterns, and escalation paths route problems to people quickly. The AI readiness assessment establishes the risk baseline before development starts, identifying where data is sensitive, where regulation applies and where mistakes would be expensive.
AI governance work then turns those findings into rules the agent system enforces. The goal is not to slow agents down but to let them move fast inside boundaries your leadership has chosen.
Teams trained by Paloren learn to work alongside these controls rather than around them.
The work, made concrete
Guardrails define what each agent may do and what needs approval
Every agent action is logged and traceable
Governance rules are set before development, not after launch
Launch is the midpoint, not the finish. Agents operate in environments that change: new tools arrive, processes shift, volumes grow. Paloren offers ongoing support starting at USD 2,500 per month for ten hours, covering monitoring, adjustments and improvements as the agent meets reality.
Support also covers the people side, because a system nobody trusts gets switched off. Team AI training helps staff understand what the agent does, where its limits sit and how to hand tasks to it or take them back.
Over time many organisations extend the pattern: a first agent proves the approach, then a second and third follow, often connected through workflow automation so they act as a coordinated system rather than isolated tools.
Paloren plans for that progression from the start, choosing architectures that expand without being rebuilt. The result is a capability that compounds, with each new agent able to reuse the foundations already in place.
The work, made concrete
Support starts at USD 2,500 per month for ten hours
Team AI training builds trust and correct use of agents
Architectures are chosen to expand without being rebuilt
A two to three week baseline from USD 8k that maps systems, data, risks and the workflows where agents could act.
Three to four weeks from USD 12k to 25k that prioritises agent use cases and sets boundaries for autonomy and approval.
Six to ten weeks from USD 40k to 90k to design the agent loop, develop it and test it against real scenarios.
Connections to CRM, communication channels and data sources, with permissions, logging and human approval points configured before go-live.
Guardrails and monitoring locked in, teams trained to work alongside agents, and ongoing support from USD 2,500 per month for ten hours.
| Service | Typical range (USD) | Typical duration |
|---|---|---|
| AI agents | 40k-90k | 6-10 weeks |
| Workflow automation and integrations | 15k-60k | 3-8 weeks |
| AI voice agents and receptionists | 25k-60k | 4-8 weeks |
| AI chatbots | 20k-50k | 4-8 weeks |
| CRM implementation with AI | 20k-80k | 4-10 weeks |
| Company brain | 60k-150k | 8-12 weeks |
| Custom apps | From 40k | Scoped during planning |
A first project typically falls between USD 25k and 100k over 2 to 10 weeks.
Paloren published service ranges
| Factor | Effect on the build |
|---|---|
| Number of connected systems | Each CRM, tool or data source adds design, testing and governance work |
| Level of autonomy | Agents that act without approval need stronger guardrails and monitoring |
| Data readiness | Clean, connected data shortens development, while fragmented data extends it |
| Approval and compliance needs | Consequential decisions require audit trails and human checkpoints |
| Scope of the first release | A focused first agent ships faster than a broad multi-agent program |
Only the published ranges above are fixed figures; everything else is scoped per engagement.
Production-ready autonomous agents deployed inside your systems
An integration layer linking agents to CRM, communication tools and data sources
A governance framework covering guardrails, logging, approval points and monitoring
Team AI training so staff can direct, supervise and trust the agents
Documentation and handover that let your organisation operate and extend the system
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 connects the workflow an agent will run, the systems it may touch and the controls that keep it accountable before autonomous code is deployed into live operations.
| Step | Stage | What it changes |
|---|---|---|
| 01 | Signal | Inventory recurring workflows, reporting tasks, CRM steps and call-analysis jobs that still consume staff hours each week. |
| 02 | Synthesis | Define each agent's objective, the decisions it may make alone, its tool list and the escalation path to named owners. |
| 03 | System | Integrate the agent with CRM, reporting and content systems, then test goal pursuit, failure paths and self-checking behaviour against historical cases. |
| 04 | Scale | Track output quality, correction effort and handover time as the agent runs, extending it one workflow at a time under governance. |
Agentic AI describes software that pursues goals on your behalf. Instead of waiting for a fixed trigger, an agent plans a sequence of steps, uses the tools and data it is connected to, checks its own results and adapts when conditions change.
Paloren builds these systems so they operate inside real business workflows, with guardrails and human approval points where judgement matters.
A chatbot answers questions in a conversation and stops there. An agent acts: it can update a CRM record, trigger a workflow, analyse a call, compile a report or handle an inbound phone call end to end.
Paloren builds both, with chatbot deployments at USD 20k to 50k over four to eight weeks and agent builds at USD 40k to 90k over six to ten weeks.
Paloren designs agents to take over tasks, not roles. Repetitive work such as data entry, report assembly, call logging and first-line responses moves to software, while people keep the decisions that need context, relationships or accountability.
Every deployment includes human approval points and team AI training, so staff shift toward supervising and improving the systems rather than competing with them.
First projects at Paloren typically range from USD 25k to 100k over two to ten weeks, depending on scope. A focused agent build sits at USD 40k to 90k over six to ten weeks, while narrower automation runs USD 15k to 60k over three to eight weeks.
An AI readiness assessment, often the starting point, begins at USD 8k over two to three weeks.
Yes. Integration is built into every engagement. Agents connect to CRM platforms, communication channels, data sources and internal tools, and they are designed around the systems you already run rather than demanding a replacement.
Where a gap exists, Paloren can build custom apps starting at USD 40k so people and agents share one interface. Every connection carries permissions, logging and escalation rules.
That is a common starting point and exactly what the AI readiness assessment addresses. Over two to three weeks, Paloren maps your systems, data quality and risks, then identifies which workflows are ready for agents and which need preparation first.
AI strategy work, USD 12k to 25k over three to four weeks, turns those findings into a sequenced plan so development begins on solid ground.
Ongoing support starts at USD 2,500 per month for ten hours, covering monitoring, tuning and improvements as the agent meets live conditions. Support includes the human side too: team AI training helps staff understand what the agent handles, where its limits sit and how to escalate.
Many organisations use early months to extend the pattern with additional agents and automation.
Paloren serves businesses worldwide, and engagements are organised at a country level rather than around office locations. The same services, from strategy through development, integration, governance and training, apply wherever your operations sit.
Agent projects are scoped against your systems and workflows, so delivery follows how your business runs rather than where it happens to be based.
Which workflow should an agent own first?
Book an AI readiness assessment
