Company/Engagement Models
Scope · Budget · Velocity · Ownership

Six ways to work with VARP. One delivery standard.

Choose the structure that matches your risk profile: validate an AI idea, lock a board-approved budget, flex a delivery team, build internal capability, hire proven engineers, or keep improving after launch.

Find your modelTalk to our team
Engagement selector
Start in the right lane.

Every model can evolve as the engagement matures.

01

Discovery Sprint

Validate

6-8 weeks

02

Fixed Price Agile

Predict

8-24 weeks

03

Time & Material

Adapt

3-18+ months

04

BOT / C2H / Retainer

Scale

Long-term

6
Models
5-10
Days to start
100+
Engineers

Find your fit

Not sure where to start?
Find yourself here.

Every engagement starts with a conversation - but these six situations map directly to specific models. If your situation matches one of these, that is likely the right starting point.

If your situation is

"I have an AI idea but I am not sure if the data supports it or what it will cost."

Start with
01 - AI Discovery Sprint
Fixed-fee · 6-8 weeks · De-risk first
If your situation is

"I have a clearly defined product to build and I need a fixed budget to take to my board."

Start with
02 - Fixed Price in Agile
Defined scope · Fixed cost · Milestone delivery
If your situation is

"The requirements will evolve. I need a team that can adapt as we learn."

Start with
03 - Time & Material
Flexible scope · Pay as you go · Best for complex AI
If your situation is

"I want to build an in-house capability long-term but do not have the team yet."

Start with
04 - BOT Model
Build · Operate · Transfer to your team
If your situation is

"I need engineers now but I may want to hire some of them permanently later."

Start with
05 - Contract to Hire
Embed first · Hire if it works · Zero recruitment risk
If your situation is

"We have launched. I need a team that stays engaged and keeps improving what we have built."

Start with
06 - Continuous Delivery Partner
Retainer · No SOW delays · Always-on

The six models

In detail. Every model explained.

Each model below includes what is included, what you need to bring, typical duration, and who it is best suited for.

01 - AI Discovery Sprint

Validate the business case before committing to the build

"We run the experiment. You get the evidence."

Most enterprise AI initiatives fail because the use case was never properly validated - the data was not ready, the ROI was not credible, or the governance requirements were not understood until it was too late to change the architecture. A Discovery Sprint closes this gap. It is a fixed-scope, fixed-fee engagement designed to produce a single output: a go/no-go decision with the evidence to defend it to your board.

Best for

Organisations with an AI ambition but no validated use case. Enterprises who need a business case before committing budget. Anyone who has watched an AI pilot fail and wants to do it properly this time.

What's included
Use case prioritisation and ROI modelling
Data readiness and quality assessment
Technical feasibility and architecture options
Governance and compliance gap analysis
Go/no-go recommendation with documented rationale
Production roadmap and team structure if positive
Duration 6-8 weeks
Pricing Fixed fee
Team 2-3 senior engineers
Start with a Discovery Sprint
discovery output
Claims processing automationScore 92
ROI potentialHigh
Data readiness assessment61% -> 94%
Recommendation: GOReady
6wk
To decision
3x
Validated use cases
fixed output
Sprint 1 - FoundationComplete
Sprint 2 - Core featuresComplete
Sprint 3 - AI integrationIn progress
Sprint 4 - QA & deploymentUpcoming
02 - Fixed Price in Agile

Defined scope. Fixed cost. Delivered in sprints.

"Board-approved budget. Agile delivery. No surprises."

Fixed price does not mean fixed process. We combine the budget predictability that CFOs and procurement teams require with the iterative, adaptive delivery that complex engineering demands. The scope is agreed upfront, the price is locked, and the delivery is structured as two-week sprints with working software at the end of each one.

Best for

Organisations with a well-defined product brief and a fixed budget for a specific phase of delivery. Ideal for product builds, platform migrations, and AI systems with clear scope.

What's included
Fixed-price proposal based on defined scope and acceptance criteria
Two-week sprint delivery with working software at each milestone
Sprint reviews and transparent progress reporting
Change control process for scope variations
Full handover documentation and IP assignment on completion
Duration 8-24 weeks typical
Pricing Fixed fee on scope
Team 3-8 engineers
Discuss a fixed-price engagement
03 - Time & Material

Maximum flexibility for evolving requirements

"Pay for what is built. Change direction when you need to."

AI programmes, complex platform migrations, and multi-system integrations rarely arrive with a complete specification on day one. Time & Material gives you the engineering capacity and expertise to move continuously - without the friction of re-scoping a fixed-price contract every time something changes.

Best for

Complex AI programmes where the full scope cannot be defined upfront. Multi-phase digital transformation. R&D-intensive work. Organisations who need to move fast and adjust as they learn.

What's included
Agreed team composition and daily or weekly rates
Weekly delivery reports and burn tracking
Flexible team scaling up or down by sprint
Full visibility into hours, progress, and blockers
Monthly billing with detailed time allocation
Duration 3-18+ months
Pricing Rate card
Team Flexible
Explore T&M engagement
tm output
47sp
Story points this sprint
+18%
Vs last sprint
AI pipeline - scope updatedAdapted
New integration requirement addedIn scope
Team scaled from 4 -> 6 engineersScaled
bot output
Phase 1 - Build completeDone
Phase 2 - Operate & optimiseMonth 8
Phase 3 - Transfer to client teamMonth 12+
12eng
Team size
18mo
Transfer timeline
04 - BOT Model

Build it. Run it. Then hand it to your team.

"We create the capability. You own it permanently."

Build-Operate-Transfer is a long-term strategic model for organisations who want to develop a permanent internal engineering or AI capability - but do not have the time, talent pipeline, or institutional knowledge to build it themselves from scratch.

Best for

Enterprise organisations making a long-term commitment to AI or engineering as a core capability. Companies expanding into new markets. Organisations who want VARP's engineering culture embedded permanently.

Three phases
Build: VARP builds the team, infrastructure, and delivery process from scratch
Operate: VARP runs the team and systems, optimising and proving the model
Transfer: Full knowledge transfer, documentation, and team handover to the client
Duration 12-24 months
Pricing Monthly retainer
Team 8-20 engineers
Discuss a BOT engagement
05 - Contract to Hire

Embed first. Hire the ones who prove themselves.

"Zero recruitment risk. Full delivery velocity from day one."

Hiring senior engineers permanently is slow, expensive, and uncertain - especially for AI and platform roles where the talent market is competitive. Contract to Hire reverses the sequence: the engineer joins as a VARP-employed contractor, delivers on a real engagement, and after a defined period you have the option to convert them to a permanent hire.

Best for

Companies building or expanding an internal engineering team. Organisations who need immediate delivery velocity while building a permanent capability. Those who have been burned by bad hires in technical roles.

What's included
Pre-vetted, senior VARP engineers on a defined contract
Immediate delivery contribution from week one
VARP-managed employment, compliance, and payroll during contract
Conversion option to permanent hire at defined milestone
Replacement guarantee if the fit is not right within the first 30 days
Duration 3-6 month contract
Pricing Day rate
Conversion Optional at milestone
Explore contract-to-hire
hire output
Senior AI Engineer embeddedActive
Contract week10 of 13
Conversion milestone approachingWeek 13
Continuous delivery - live
AI model drift detected - retrain queuedAuto
3 features shipped this weekDone
Inference cost optimised - 23% downLLMOps
99.9%
Uptime this month
14mo
Active partnership
06 - Continuous Delivery Partner

We stay engaged. The system keeps improving.

"A production system is not finished on launch day."

A launched AI system is not a finished product - it drifts, degrades, accumulates technical debt, and requires continuous improvement to maintain the business case it was built on. VARP offers a retainer-based continuous delivery model where we stay as an integrated engineering partner.

Best for

Clients who have launched a system with VARP or another firm and want to maintain delivery velocity without rebuilding a new engagement from scratch. Organisations with complex AI systems that require active monitoring and improvement.

What's included
Dedicated engineering capacity on a monthly retainer
Continuous feature delivery and platform improvement
AI model monitoring, drift detection, and retraining
Inference cost management and LLMOps
Monthly delivery review and roadmap alignment
Duration Month-to-month
Pricing Monthly retainer
Notice 30 days
Start a delivery partnership

How every engagement begins

From first conversation to ship & scale.

Regardless of which model you choose, every VARP engagement follows the same seven-stage journey. This is what happens after you reach out.

01
Step 01

Contact & NDA

You reach out by form, email, or direct conversation. NDA signed before commercial or technical detail is shared.

02
Step 02

Consultation

A 60-minute call with a senior VARP engineer to discuss objectives, constraints, and current state.

03
Step 03

Cost estimate

We provide a proposal with team structure, timeline, and budget estimate within 5 business days.

04
Step 04

Discovery

Objectives are broken down, key results are mapped, and technical and data requirements are identified.

05
Step 05

Constructing MVP

We build the minimum viable feature set that validates core value without accumulating avoidable technical debt.

06
Step 06

Execution

Two-week sprints, working software every cycle, quality gates at every stage, and client sprint reviews.

07
Step 07

Ship & Scale

Multistage release with quality, performance, and security testing before go-live, then monitoring and scale support.

From conversation to first engineer on ground

Typical time from initial contact to a VARP team beginning active delivery: 5-10 business days. NDA same day. Consultation within 2 days. Proposal within 5 days.

Side-by-side comparison

All six models. Ten seconds to decide.

Scan this table to identify which model fits your situation. If two rows look equally right, start with the one that requires less upfront commitment.

AI Discovery SprintFixed Price in AgileTime & MaterialBOT ModelContract to HireContinuous Delivery
Scope defined upfrontFullFullFlexiblePhasedBy roleOngoing
Fixed budgetYesYesRate cardMonthlyDay rateRetainer
Typical duration6-8 weeks8-24 weeks3-18+ months12-24 months3-6 monthsMonth-to-month
Team size2-3 senior3-8 engineersFlexible8-20 engineers1-5 engineersAgreed retainer
Client owns IPYesYesYesYesYesYes
Can evolve to another modelCommonYesYesYesYesYes
Best entry pointIdea stageDefined scopeComplex / evolvingLong-term capabilityTalent gapPost-launch

Questions CEOs actually ask

Before you reach out. The answers are here.

Can we start small before committing to a larger engagement?+

Yes - and we actively encourage it. The AI Discovery Sprint is specifically designed as a low-commitment entry point. It produces a real, defensible output: a go/no-go recommendation and production roadmap.

What happens if the scope changes mid-engagement?+

It depends on the model. Fixed Price in Agile has a formal change control process. Time & Material has less change-control friction because scope evolves naturally and is reflected in the next billing period.

Do we own the intellectual property for everything built?+

Yes. All client-specific IP is assigned to you on final payment across all six engagement models. Pre-built accelerators and component libraries, when used, are disclosed upfront and licensed indefinitely at no ongoing cost.

How fast can you actually start?+

NDA same day. Consultation within 2 business days. Proposal within 5. Typical time from first contact to first engineer on ground is 5-10 business days.

Can we scale the team up or down during an engagement?+

Time & Material and Continuous Delivery are explicitly designed for this. Fixed Price in Agile has a fixed team composition per phase, but phases can be structured to allow scaling between them.

Ready to start

Not sure which model fits?
That is what the first call is for.

A 45-minute conversation with a senior VARP engineer - not a sales team - will tell you more about which model is right than any page can.

Book a 45-minute callSend us a brief

Responded to within 1 business day. NDA signed before anything technical is discussed.