AI Build Costs Explained by the Team That Builds Them
Paloren explains how much it costs to build an AI, with published ranges for assessments, strategy, agents, automation, company brains and support.
Founders, operations leaders and marketing teams budgeting for their first serious AI build.
Paloren prices every AI build against scope, data readiness and the systems involved. First projects typically land between USD 25k and 100k over 2 to 10 weeks, while assessments start at USD 8k.
Aaron Agius, an AI implementation consultant and a Paloren co-founder, shaped these ranges across 20 years of building growth systems. Get an assessment and you receive a costed plan before committing to a build.
Most companies asking this question mean one of four things: an AI agent, a chatbot, a set of automations, or a company brain that holds institutional knowledge. Paloren publishes a range for each.
A first AI project typically lands between USD 25k and 100k and runs 2 to 10 weeks. Entry points sit lower, with readiness assessments from USD 8k over 2 to 3 weeks and strategy engagements from USD 12k over 3 to 4 weeks.
Builds scale from there: workflow automation runs USD 15k to 60k, CRM implementation with AI runs USD 20k to 80k, chatbots run USD 20k to 50k, voice agents run USD 25k to 60k, agents run USD 40k to 90k, and a company brain spans USD 60k to 150k.
Custom apps start at USD 40k. Anyone quoting a single figure without scoping your data, systems and workflows is guessing, because the same word 'AI' can describe a two-week automation or a quarter-long knowledge platform.
The honest answer is a range tied to scope, and the fastest way to a real number is a scoped assessment.
Price follows four inputs. First, data readiness: models are only as good as the records they read, so scattered spreadsheets and disconnected tools add architecture work before any intelligence appears.
Second, integration count: every CRM, ERP or ticketing system an AI must touch adds engineering time, and legacy platforms cost more to bridge than modern ones. Third, scope breadth: automating one reporting workflow is a fraction of the effort of an agent that handles calls, updates records and escalates across departments.
Fourth, governance: regulated industries need audit trails, access controls and review steps built in from day one. Paloren prices each input openly rather than padding a single number.
That is why the published ranges span USD 8k for an assessment to USD 150k for a company brain, and why two businesses asking for 'an AI' can receive very different quotes honestly.
A scoped assessment measures these four inputs in your business and converts them into a fixed range, which removes the guesswork that makes AI budgets feel risky.
Keep these in view
| Build type | Typical cost range | Typical timeline |
|---|---|---|
| First AI project | USD 25k to 100k | 2 to 10 weeks |
| AI readiness assessment | From USD 8k | 2 to 3 weeks |
| AI strategy | USD 12k to 25k | 3 to 4 weeks |
| Company brain | USD 60k to 150k | 8 to 12 weeks |
| AI agents | USD 40k to 90k | 6 to 10 weeks |
| Workflow automation and integrations | USD 15k to 60k | 3 to 8 weeks |
| CRM implementation with AI | USD 20k to 80k | 4 to 10 weeks |
| AI chatbot | USD 20k to 50k | 4 to 8 weeks |
| AI voice agent or receptionist | USD 25k to 60k | 4 to 8 weeks |
| Custom apps | From USD 40k | Scoped at assessment |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
Every range is published upfront and confirmed after scoping.
Source: Paloren published rate ranges
| Cost factor | Keeps cost low | Pushes cost up |
|---|---|---|
| Data readiness | Clean records in one place | Data scattered across disconnected tools |
| Scope | One workflow at a time | Several teams and processes in one build |
| Integrations | Modern systems with open APIs | Legacy or custom platforms needing bridges |
| Model approach | Proven models configured to your data | Heavy customisation or fine tuning |
| Governance | Standard access and review controls | Regulated industries needing deep oversight |
| Team readiness | Staff trained to run the system | Change management and full training programmes |
Scoping fixes these factors into a fixed range before any build starts.
Source: Paloren published rate ranges
| Build type | Typical cost range | Typical timeline |
|---|---|---|
| First AI project | USD 25k to 100k | 2 to 10 weeks |
| AI readiness assessment | From USD 8k | 2 to 3 weeks |
| AI strategy | USD 12k to 25k | 3 to 4 weeks |
| Company brain | USD 60k to 150k | 8 to 12 weeks |
| AI agents | USD 40k to 90k | 6 to 10 weeks |
| Workflow automation and integrations | USD 15k to 60k | 3 to 8 weeks |
| CRM implementation with AI | USD 20k to 80k | 4 to 10 weeks |
| AI chatbot | USD 20k to 50k | 4 to 8 weeks |
| AI voice agent or receptionist | USD 25k to 60k | 4 to 8 weeks |
| Custom apps | From USD 40k | Scoped at assessment |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
| Cost factor | Keeps cost low | Pushes cost up |
|---|---|---|
| Data readiness | Clean records in one place | Data scattered across disconnected tools |
| Scope | One workflow at a time | Several teams and processes in one build |
| Integrations | Modern systems with open APIs | Legacy or custom platforms needing bridges |
| Model approach | Proven models configured to your data | Heavy customisation or fine tuning |
| Governance | Standard access and review controls | Regulated industries needing deep oversight |
| Team readiness | Staff trained to run the system | Change management and full training programmes |
Two small engagements protect the big one. A readiness assessment costs from USD 8k and runs 2 to 3 weeks, auditing your data quality, existing tools, workflow candidates and team capability.
It produces a ranked list of AI opportunities with estimated effort and payback, so budget flows to the work that returns fastest.
AI strategy follows at USD 12k to 25k over 3 to 4 weeks where the picture is more complex, turning assessment findings into a sequenced roadmap with architecture decisions, governance guardrails and training plans.
Skipping these stages is how companies end up paying twice: a build started without scoping often needs rework once the real data problems surface mid-project.
Paloren treats the pre-build phase as the cheapest risk reduction available in AI, because moving a line on a roadmap costs nothing while moving a built system costs weeks.
Businesses that complete assessment and strategy typically enter their first build with a fixed scope, a fixed range and a shortlist of integrations already validated.
Keep these in view
A company brain is the most substantial build Paloren delivers, priced at USD 60k to 150k over 8 to 12 weeks. It is a central knowledge system that connects your documents, conversations, CRM records and reporting into one place a team can question directly.
Staff ask it for pricing history, campaign performance, process steps or account context and receive answers grounded in company data rather than general model knowledge.
The cost reflects three things: connecting every relevant source, designing retrieval so answers stay accurate, and building access controls so sensitive information reaches only the right people.
Companies choose it when knowledge sits in silos and senior people become bottlenecks for basic questions. A lighter path exists: chatbots at USD 20k to 50k handle narrower question sets, and agents at USD 40k to 90k execute specific workflows.
The company brain earns its range when many teams need many answers from many systems, which is also why it demands the longest timeline on the list at up to 12 weeks.
Keep these in view
Execution systems carry mid-range prices with clear differences. Workflow automation and integrations run USD 15k to 60k over 3 to 8 weeks, moving data between tools and removing manual steps such as lead routing, report assembly or data entry.
Chatbots cost USD 20k to 50k over 4 to 8 weeks and answer questions on your site or inside your platforms using your own content. Voice agents and AI receptionists run USD 25k to 60k over 4 to 8 weeks, handling inbound calls, booking and routing with natural conversation.
Full AI agents sit at USD 40k to 90k over 6 to 10 weeks because they decide and act: reading call transcripts, updating the CRM, drafting responses and escalating exceptions to humans.
The dividing line is autonomy. Automation follows fixed rules, a chatbot answers, a voice agent converses, and an agent reasons across systems. Paloren helps companies pick the cheapest category that solves the problem, which is why automation often precedes agents on a roadmap and keeps the first invoice smaller.
Keep these in view
Build budgets are one-off; running costs are recurring. Paloren support starts at USD 2,500 per month for 10 hours, covering monitoring, model tuning, prompt refinement, integration checks and small enhancements.
AI systems need this care because inputs drift: pricing changes, new documents appear, a CRM field gets renamed and an unmonitored system quietly degrades. Monthly support keeps answers accurate and catches failures before staff lose trust in the tool.
Beyond support, running costs include model usage, which scales with volume, and periodic training as new team members join or new workflows ship. in-house", "business-critical, and Paloren documents systems thoroughly to make that possible.
Others keep a retainer because their build is business critical. Either path is valid, and the choice is made openly at handover rather than locked in. What matters for budgeting is this: the build price buys the system, the monthly line keeps it healthy, and the governance framework defines who watches what.
Keep these in view
Paloren combines implementation, workflow design and practical team training. That history shapes pricing in a specific way: estimates account for the messy realities of real stacks, real permissions and real teams, not clean demo environments.
Companies pay for ranges that hold, governance that satisfies serious stakeholders and training that makes systems stick. Enterprise-grade experience does not mean enterprise-only prices, since published ranges start at USD 8k for an assessment and USD 25k to 100k for a first project.
Keep these in view
Precise numbers come from scoping, and scoping starts with the readiness assessment at USD 8k. Over 2 to 3 weeks Paloren audits your data, systems, workflows and team capability, then returns a ranked opportunity list with costed options.
You see which builds fit the USD 15k automation band, which need the USD 40k to 90k agent tier and whether a company brain at USD 60k to 150k is justified. Strategy can follow at USD 12k to 25k to sequence those options into a roadmap, or you can move straight to a scoped first project between USD 25k and 100k.
Every quote itemises integrations, governance, training and support so nothing hides in a blended fee. Paloren serves businesses worldwide and delivers the whole process remotely, so location never blocks a scoped estimate.
The practical move is simple: book the assessment, receive the costed roadmap and fund the build that pays back first with full visibility of timeline, price and scope.
Keep these in view
Changes happen, and honest pricing plans for them. During assessment and strategy, Paloren defines the build in phases so the first phase delivers value on its own and later phases extend it.
If new requirements surface mid-build, for example a second integration or an extra workflow, the change is estimated against the same published ranges rather than invented day rates.
Small adjustments often fit inside the existing range; larger ones become a scoped addition with their own timeline.
This phased approach is also why first projects run 2 to 10 weeks at USD 25k to 100k rather than one giant engagement: shorter builds give earlier feedback, and feedback reduces the chance of building the wrong thing.
Companies coming from big agency or software experiences will recognise the discipline. What they may not expect is how much cost control comes from simply shipping the highest value workflow first, then deciding with evidence whether the second one is worth funding at all.
Keep these in view
A 2 to 3 week audit of data, tools and workflows, from USD 8k, that shows where AI will pay back first.
A 3 to 4 week roadmap at USD 12k to 25k that sequences builds, budgets and governance before development begins.
Paloren converts the roadmap into a fixed scope, timeline and price, usually within the USD 25k to 100k band for first projects.
The chosen system, whether agents, automation or a company brain, is built, tested and connected to your existing stack.
Team AI training plus optional support from USD 2,500 per month for 10 hours keeps performance steady after launch.
Readiness assessment report with costed build recommendations
AI strategy roadmap with sequenced budgets and governance
Working AI agents, automations or a company brain deployed in your stack
Documented integrations across your CRM and data tools
AI governance framework with access and review controls
Team AI training sessions and optional support from USD 2,500 per month
| Build type | Typical cost range | Typical timeline |
|---|---|---|
| First AI project | USD 25k to 100k | 2 to 10 weeks |
| AI readiness assessment | From USD 8k | 2 to 3 weeks |
| AI strategy | USD 12k to 25k | 3 to 4 weeks |
| Company brain | USD 60k to 150k | 8 to 12 weeks |
| AI agents | USD 40k to 90k | 6 to 10 weeks |
| Workflow automation and integrations | USD 15k to 60k | 3 to 8 weeks |
| CRM implementation with AI | USD 20k to 80k | 4 to 10 weeks |
| AI chatbot | USD 20k to 50k | 4 to 8 weeks |
| AI voice agent or receptionist | USD 25k to 60k | 4 to 8 weeks |
| Custom apps | From USD 40k | Scoped at assessment |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
Every range is published upfront and confirmed after scoping.
Paloren published rate ranges
| Cost factor | Keeps cost low | Pushes cost up |
|---|---|---|
| Data readiness | Clean records in one place | Data scattered across disconnected tools |
| Scope | One workflow at a time | Several teams and processes in one build |
| Integrations | Modern systems with open APIs | Legacy or custom platforms needing bridges |
| Model approach | Proven models configured to your data | Heavy customisation or fine tuning |
| Governance | Standard access and review controls | Regulated industries needing deep oversight |
| Team readiness | Staff trained to run the system | Change management and full training programmes |
Scoping fixes these factors into a fixed range before any build starts.
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.
Budgeting an AI starts with knowing whether you are buying an automation, a chatbot, an agent or a company brain. S4 turns that ambiguity into scoped, priced stages.
| Step | Stage | What it changes |
|---|---|---|
| 01 | Signal | Audit data readiness, count CRM and ERP integrations, list workflow candidates and note governance needs like audit trails. |
| 02 | Synthesis | Convert the four price inputs into a scope choice: workflow automation, chatbot, voice agent, agent or company brain. |
| 03 | System | Test the build against real records and systems, from a USD 15k automation through a USD 150k knowledge platform. |
| 04 | Scale | Assign an operations owner to track integration count, data quality and support load, extending scope one workflow at a time. |
A readiness assessment is the lowest cost entry point, starting at USD 8k over 2 to 3 weeks. It audits your data, tools and workflows, then identifies which builds deserve budget.
Strategy at USD 12k to 25k over 3 to 4 weeks turns those findings into a sequenced roadmap, so you commit to a build only once the business case is clear.
AI agents at Paloren run USD 40k to 90k over 6 to 10 weeks. The range reflects what the agent must do: a narrow agent that drafts reports costs far less than one that reads calls, updates a CRM and escalates exceptions across departments.
Every agent quote is built from the workflows it replaces, the systems it touches and the oversight it needs, which is why scoping comes first.
Timelines follow scope. A readiness assessment takes 2 to 3 weeks, strategy takes 3 to 4 weeks, workflow automation takes 3 to 8 weeks, chatbots and voice agents take 4 to 8 weeks, AI agents take 6 to 10 weeks and a company brain takes 8 to 12 weeks.
Most first projects complete within 2 to 10 weeks, and Paloren sequences larger programmes into phases so value ships early.
Yes. Paloren support starts at USD 2,500 per month for 10 hours, covering monitoring, model tuning, prompt refinement and small enhancements. AI systems drift as your data, pricing and workflows change, so budgeting for ongoing care keeps performance steady.
Some businesses run support inhouse after handover; others keep Paloren on retainer. Either way, the build price is one-off and support is sized to how critical the system is.
Two companies can both ask to 'build me AI' and receive very different quotes. The difference sits in data readiness, the number of systems to integrate, governance requirements and how many workflows the build must cover.
A company with clean centralised records and one clear use case sits at the low end. A business with scattered data, legacy platforms and compliance obligations needs more architecture, testing and governance before launch.
Yes. AI strategy is a standalone engagement at USD 12k to 25k over 3 to 4 weeks. You receive a costed roadmap covering priorities, architecture, governance and training, which your team can execute or bring back to Paloren.
Many companies start there, run the assessment first at USD 8k, and then decide which builds to fund. There is no obligation to proceed into implementation with Paloren afterwards.
Plan between USD 25k and 100k for a first build, delivered over 2 to 10 weeks. That range covers the majority of first projects Paloren scopes, whether an automation set, a chatbot or a focused agent.
Adding a readiness assessment from USD 8k before the build usually saves money overall, because it removes speculative scope. Companies wanting a company brain should plan separately at USD 60k to 150k.
Paloren is co-founded by Aaron Agius, an AI implementation consultant, and Alex Agius. Paloren combines implementation, workflow design and practical team training.
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