A clear proposal for building AI agents that work
Paloren writes AI agent development proposals that set scope, pricing and timelines clearly. Request a proposal from Aaron Agius and the Paloren team.
Leaders preparing an AI agent development proposal and comparing providers before committing budget.
Paloren prepares AI agent development proposals that define scope, architecture, timeline and investment before any build starts. Aaron Agius, an AI implementation consultant, co-founded Paloren with Alex Agius and leads every proposal personally.
Agent engagements typically range from USD 40k to 90k over 6 to 10 weeks, with the exact figure fixed inside your written proposal.
An AI agent development proposal is a written document that defines what an agent will do inside your business, how it will be built, what it will connect to, how long the work will take and what it will cost.
It sits between an initial conversation and a signed engagement. Instead of agreeing to vague 'AI work', you receive a specific plan: the agent's responsibilities, the systems it will touch, the guardrails around its actions, the phases of delivery and a price attached to each phase.
A good proposal also states what is excluded, so nobody discovers mid-project that a critical integration was never counted. Paloren treats the proposal as the foundation of the engagement rather than a sales formality.
Because agent projects change how work gets done across teams, the document needs to be precise enough that operations, technology and finance leads can all read the same pages and reach the same conclusion.
That precision is what separates a proposal you can act on from a pitch deck you soon forget.
The work, made concrete
A written definition of scope before any commitment
Phase by phase pricing tied to deliverables
Explicit exclusions so nothing surprises you mid build
Paloren starts with a written proposal because agent projects touch many parts of a business at once, and informal agreements break down under that complexity. A proposal carries that same discipline into your project.
It forces the hard questions early: which systems the agent will touch, who approves its actions, what happens when it encounters an edge case and how success will be measured.
Answering those questions on paper costs far less than answering them mid-build. It also gives your internal stakeholders something concrete to review and approve, which shortens internal debate.
By the time development begins, everyone involved has read the same document and agreed to the same plan.
| Service | Investment range | Typical duration |
|---|---|---|
| AI readiness assessment | From USD 8k | 2 to 3 weeks |
| AI strategy | USD 12k to 25k | 3 to 4 weeks |
| AI agents | USD 40k to 90k | 6 to 10 weeks |
| Workflow automation and integrations | USD 15k to 60k | 3 to 8 weeks |
| Company brain | USD 60k to 150k | 8 to 12 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 agents and receptionists | USD 25k to 60k | 4 to 8 weeks |
| Custom apps | From USD 40k | Scoped per proposal |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
Ranges Paloren quotes in proposals; a first project generally sits between USD 25k and 100k over 2 to 10 weeks.
Source: Paloren published service ranges
| Proposal section | What it covers | Why it matters |
|---|---|---|
| Executive summary | The agent, the outcome and the investment on one page | Lets decision makers align quickly |
| Current state findings | What discovery found in your workflows and systems | Grounds the design in evidence |
| Agent architecture | The agents, models, tools and integrations proposed | Shows exactly what gets built |
| Delivery plan | Phases, milestones and responsibilities across weeks | Sets expectations for the build |
| Investment breakdown | Costs by phase using the published ranges | Removes ambiguity about price |
| Governance and risk | Access controls, oversight and review points | Keeps deployment accountable |
| Assumptions and exclusions | What the price includes and what sits outside scope | Prevents disputes later |
Each proposal follows a consistent structure so comparison across options is straightforward.
Source: Paloren published service ranges
The work, made concrete
Agent projects span teams, so scope must be explicit
Early answers cost less than mid-build corrections
Every Paloren proposal follows a consistent structure so your team can evaluate it quickly. It opens with an executive summary that states the agent's purpose, the outcome it targets and the total investment on a single page.
Findings from discovery come next, describing what we learned about your workflows, data and systems before any design was drawn. The core of the document is the agent architecture: which agents are proposed, what tools and models they use, which platforms they integrate with and how human oversight works.
A delivery plan then breaks the build into phases with milestones and named responsibilities. Investment is shown as a breakdown by phase, drawn from the ranges below, so you can see where the money goes rather than receiving one opaque number.
Governance and risk controls appear in their own section, covering access, monitoring and review points. Finally, assumptions and exclusions make the boundary of the quote explicit.
Together these sections turn a conversation about AI agents into a document your board can approve.
The work, made concrete
Executive summary, findings, architecture and plan in one document
Phase level investment breakdown with no hidden numbers
Governance, assumptions and exclusions stated up front
Accurate proposals come from accurate inputs, so Paloren invests in discovery before writing a single line of scope. The process starts with a discovery call covering your goals, the processes you want agents to handle, the systems involved and the constraints around data and approvals.
Where deeper evidence is needed, we recommend an AI readiness assessment, which runs from USD 8k over 2 to 3 weeks and examines your data quality, tooling, security posture and team capability.
For organisations that already know their landscape, a lighter discovery phase may be enough. The output of this stage is an opportunity map: candidate agent use cases ranked by impact and feasibility, each with the systems it would touch and the risks it would carry.
You review that map before the proposal is written, which means the document you receive describes work you have already shaped. Nothing in the final proposal should feel like it arrived from nowhere.
The work, made concrete
Discovery call covering goals, processes and systems
Optional readiness assessment from USD 8k over 2 to 3 weeks
Opportunity map reviewed with you before the proposal is written
Paloren prices agent work against scope, not against a generic day rate. Agent engagements typically fall between USD 40k and 90k and run 6 to 10 weeks, with the final figure shaped by a handful of factors.
The number of distinct agents matters, because each one carries its own design, testing and oversight load. Integration depth matters even more: an agent that reads one system costs less to build than one that acts across five.
The sophistication of the reasoning required, the volume of traffic the agent must handle and the amount of human review built into its workflow all move the price.
Where agents sit alongside other work, such as workflow automation from USD 15k to 60k or CRM implementation with AI from USD 20k to 80k, the proposal prices each component separately so you can phase spending.
A first project with Paloren generally lands between USD 25k and 100k over 2 to 10 weeks depending on what it contains. Every figure in your proposal is fixed before you sign.
The work, made concrete
Agent builds typically range from USD 40k to 90k over 6 to 10 weeks
Integration depth and agent count drive the final figure
First projects generally sit between USD 25k and 100k over 2 to 10 weeks
Two proposals for 'an AI agent' can differ by a wide margin, and the difference almost always traces back to a few identifiable factors.
Breadth of responsibility comes first: an agent that drafts content for human review is a lighter build than one that updates records, triggers payments and communicates with customers on its own.
System landscape comes second. Clean, well documented platforms connect quickly, while fragmented environments need integration work before agents can act, which is why some proposals include workflow automation priced from USD 15k to 60k.
Data readiness is third, since agents that draw on a company brain, ranging from USD 60k to 150k over 8 to 12 weeks, depend on knowledge being organised first.
Channel also matters: a text chatbot sits between USD 20k and 50k, while voice agents and receptionists run from USD 25k to 60k because speech adds design and testing load.
Your proposal names the factors that apply to you, so the price is explainable line by line.
The work, made concrete
Autonomy level and breadth of responsibility
State of your systems and required integrations
Channel choice: chatbot, voice agent or multi system agent
The proposal stage has two halves: the time Paloren needs to produce the document, and the time your team needs to review it. On our side, duration tracks the depth of discovery.
A light discovery may be enough when your systems and goals are already clear, while a full readiness assessment runs 2 to 3 weeks and a strategy engagement runs 3 to 4 weeks where direction needs setting before agents are scoped.
Once discovery closes, the proposal itself is written promptly while findings are fresh. On your side, review speed depends on how many stakeholders need to read the document.
Proposals that name a single decision maker move faster than those circulating through committees. Paloren supports the review with a walkthrough session, answering questions directly rather than leaving your team to interpret the pages alone.
From first call to signed proposal, most agent engagements move at the pace your own approval process sets.
The work, made concrete
Discovery depth sets the production timeline
Readiness assessment runs 2 to 3 weeks; strategy runs 3 to 4
A walkthrough session speeds up your internal review
Accepting a proposal converts the document into a delivery plan. The phases described on paper become scheduled work, beginning with any foundations the proposal identified, such as access to systems, data preparation or integration groundwork.
Agent builds then follow the sequence set out in the delivery plan, typically running 6 to 10 weeks for agent engagements within the USD 40k to 90k range. Each phase closes with a checkpoint against the milestones named in the proposal, so progress is measured against the document rather than against shifting expectations.
Where the proposal bundled several components, for example agents alongside workflow automation or CRM implementation with AI, the phases run in the order that de-risks the whole programme.
After launch, support is available from USD 2,500 per month for 10 hours, covering monitoring, refinements and the adjustments that real usage always reveals. The proposal does not expire at kickoff; it remains the reference point for scope conversations throughout the engagement.
The work, made concrete
Phases become scheduled work with named milestones
Agents typically build over 6 to 10 weeks
Support available from USD 2,500 per month for 10 hours
Proposals at Paloren are written by the people who will deliver the work. Aaron Agius, an AI implementation consultant, co-founded Paloren with Alex Agius and leads the design of every agent engagement.
Alex Agius works alongside Aaron in shaping how engagements are scoped. Paloren combines implementation, workflow design and practical team training. That combination keeps the document grounded: ambitious enough to change how you work, realistic enough to survive contact with your calendar.
The work, made concrete
Aaron Agius leads the design of every agent engagement
Co-author of Faster, Smarter, Louder, published in 2019
Team experience inside IBM, Ford, LG, Unilever, Jaguar and Chelsea FC
If you are collecting proposals from more than one provider, comparison works best against structure rather than charisma. Start with scope: does each document define exactly which systems the agent touches, which actions it takes autonomously and which require human approval?
Vague scope is the most common source of cost overruns. Next, examine the pricing logic. A proposal that shows a breakdown by phase lets you see what you are buying, while a single round number hides the assumptions inside it.
Check the delivery plan for named milestones and review points, since these are what let you hold the engagement to account. Look for governance: access controls, monitoring and a clear statement of what the agent must never do.
Finally, weigh the people behind the document. A proposal is only as strong as the team that must honour it.
The work, made concrete
Scope precision: named systems, named actions, named approvals
Pricing broken down by phase rather than one round number
Governance and the track record of the delivery team
A structured session covering goals, processes, systems and constraints, so candidate agent use cases are on the table from day one.
Where needed, an assessment of data quality, tooling, security and team capability, running from USD 8k over 2 to 3 weeks.
Mapping the proposed agents, their tools and integrations, oversight points and the sequence in which components should be built.
Documenting scope, architecture, phases, investment, governance, assumptions and exclusions in a single document for your stakeholders.
A live session to answer questions and adjust detail, followed by a fixed quotation your team can approve with confidence.
| Service | Investment range | Typical duration |
|---|---|---|
| AI readiness assessment | From USD 8k | 2 to 3 weeks |
| AI strategy | USD 12k to 25k | 3 to 4 weeks |
| AI agents | USD 40k to 90k | 6 to 10 weeks |
| Workflow automation and integrations | USD 15k to 60k | 3 to 8 weeks |
| Company brain | USD 60k to 150k | 8 to 12 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 agents and receptionists | USD 25k to 60k | 4 to 8 weeks |
| Custom apps | From USD 40k | Scoped per proposal |
| Ongoing support | From USD 2,500 per month | 10 hours monthly |
Ranges Paloren quotes in proposals; a first project generally sits between USD 25k and 100k over 2 to 10 weeks.
Paloren published service ranges
| Proposal section | What it covers | Why it matters |
|---|---|---|
| Executive summary | The agent, the outcome and the investment on one page | Lets decision makers align quickly |
| Current state findings | What discovery found in your workflows and systems | Grounds the design in evidence |
| Agent architecture | The agents, models, tools and integrations proposed | Shows exactly what gets built |
| Delivery plan | Phases, milestones and responsibilities across weeks | Sets expectations for the build |
| Investment breakdown | Costs by phase using the published ranges | Removes ambiguity about price |
| Governance and risk | Access controls, oversight and review points | Keeps deployment accountable |
| Assumptions and exclusions | What the price includes and what sits outside scope | Prevents disputes later |
Each proposal follows a consistent structure so comparison across options is straightforward.
A written proposal covering scope, architecture, phases and investment
An agent opportunity map ranked by impact and feasibility
A phase by phase investment breakdown with no hidden numbers
A governance and oversight outline for every proposed agent
A walkthrough session with Aaron Agius and the delivery team
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.
A proposal defines the agent's responsibilities, systems it will touch, guardrails, delivery phases and price before development begins. S4 shapes that document so operations, technology and finance leads reach the same conclusion.
| Step | Stage | What it changes |
|---|---|---|
| 01 | Signal | Capture the agent's intended responsibilities, systems it will touch, edge cases encountered today and the outcome each phase must target. |
| 02 | Synthesis | Draft the executive summary, phase-by-phase scope, approval matrix for agent actions and explicit exclusions so nothing critical goes uncounted. |
| 03 | System | Attach a price to each delivery phase, define guardrails, sequence integrations and state how success will be measured once the agent runs. |
| 04 | Scale | Have internal stakeholders review and approve the document, then extend the agent one phase at a time as operations adapt. |
Agent engagements at Paloren typically range from USD 40k to 90k and run 6 to 10 weeks. The final figure depends on how many agents you need, how many systems they must connect to and how much autonomy they carry.
Your proposal fixes the price before you sign, with a breakdown by phase so you can see exactly what each portion of the budget buys.
A chatbot handles conversations, answering questions and routing requests within a defined scope, and Paloren builds these from USD 20k to 50k over 4 to 8 weeks. An AI agent goes further, taking actions across your systems such as updating records, triggering workflows or completing multi-step tasks with oversight.
That added capability is why agent engagements range from USD 40k to 90k over 6 to 10 weeks.
Not always, but it helps when your data, tooling or governance posture is untested. The assessment runs from USD 8k over 2 to 3 weeks and examines data quality, systems, security and team capability.
Where the landscape is already understood, a lighter discovery call may be enough. Paloren recommends the path that produces the most accurate proposal rather than the largest first invoice.
Yes. Many proposals bundle AI agents with workflow automation and integrations, CRM implementation with AI or a company brain, because these components often depend on each other.
Each element is priced separately within the document, using the published ranges, so you can approve everything at once or phase the work. Bundling also lets the delivery sequence be designed as one coherent programme rather than separate projects.
Aaron Agius, an AI implementation consultant, co-founded Paloren with Alex Agius and leads proposal design personally. Paloren combines implementation, workflow design and practical team training.
You work with the same people who would deliver the build, which keeps the proposal honest about what the work actually involves.
Yes. Proposals can include a support option starting from USD 2,500 per month for 10 hours. That covers monitoring, refinements and adjustments as real usage reveals edge cases no design can fully anticipate.
Agents that act across live systems need attention after launch, and the support arrangement means the team that built your agents stays accountable for how they behave in production.
Yes. Integration sits at the centre of agent design, and Paloren offers workflow automation and integrations from USD 15k to 60k over 3 to 8 weeks alongside CRM implementation with AI from USD 20k to 80k over 4 to 10 weeks.
Your proposal states exactly which platforms the agents will connect to, how data will flow between them and what happens where a system cannot support the integration needed.
The proposal is a starting document, not a cage. If priorities shift during delivery, Paloren revises the affected phases and quotes the change before any new work begins, so the budget never drifts silently.
Because the original document lists assumptions and exclusions, most change conversations are quick: both sides can see what sat inside the original price and what sits outside it. Adjusted scope is always agreed in writing.
Yes. Paloren provides AI strategy, implementation, automation and training for companies worldwide, and the proposal process works over video with structured walkthrough sessions. Paloren combines implementation, workflow design and practical team training.
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