Delivery model

Architect quickly. Build relentlessly. Operate continuously.

Design is brief and decisive. Build & Ship with speed. Operate is where outcomes compound. Here's how we run all three.

Chapter 01 · Design

Design is brief and decisive.

Discovery to architectural lock runs days to weeks, not months. Three named steps. You leave with an honest read on what to build, why, and how. Plus the price tag and the risks named out loud.

01
Define

Current state, real pain, the business outcome we are aiming for. We start from what the business needs to do, not the last vendor’s exit memo or a spec doc.

AS-IS map · Prioritized backlog
02
Design

Shape the solution. Pressure-test feasibility and trade-offs before anyone touches a keyboard.

Solution options · Risk register
03
Architect

Design locked, business case attached, SOW that ties the technical plan to the dollars.

Solution design · Roadmap & SOW

AI-native cadenceFor AI-native work, compress the cadence: discovery in days, prototypes in a week, production in under 90 days.

Chapter 02 · Build & Ship

Build & Ship is where the engagement happens.

Multiple ways to buy delivery from Aquiva. They differ on one question: who owns what risk? With Aquiva AI POD, we own delivery; you own roadmap priorities. With Scale, we own team operation; you own roadmap and scope. With Flex, you own everything; we supply the people. With Outcome, we own the whole result: scope, time, price.

The cheaper-looking option isn't always the better one. Scale is the lowest hourly rate because the long commitment lets us load-balance utilization across the bench. Flex looks similar on paper but costs more per hour. Flexibility has a price. Aquiva AI POD isn't priced per hour at all: flat monthly for a delivery unit, with ~7% overhead instead of the ~15–25% typical on traditional capacity teams (10–20% PM allocation per Hypersense's 2025 effort-allocation study; ~25% knowledge-worker productivity drains per APQC), so per-output it often beats both. Outcome trades a premium for certainty. We absorb execution risk.

Most of the engagement, most of the energy, most of the value. Two delivery tracks: continuous teams that compound context over time, or fixed-scope projects that ship a defined result.

Project-based deliveryA defined result, shipped on a fixed timeline.
FIXED SCOPE, FIXED PRICE

Outcome

A defined scope, a fixed price, a fixed timeline. You buy the result; we absorb execution risk.

  • Scope locked up front. No surprises mid-flight.
  • Fixed price tied to the result, not hours burned.
  • Milestone-based delivery you can plan around.
  • One team accountable for shipping, end to end.

"Tell me the price, tell me the date, ship the thing."

Project-basedFixed scopeFixed priceFixed timeline
Continuous deliverySame people, learning the work over months.
New offering
AI-NATIVE DELIVERY

Aquiva AI POD

A managed delivery unit built around AI leverage. You set roadmap priorities; the pod handles decomposition, building, shipping, and communication. You're not buying headcount. You're buying a unit designed to outpace one.

  • ~7% overhead vs. ~15–25% typical on traditional capacity teams (Hypersense 2025; APQC). AI leverage compounds across every cycle.
  • 1 Orchestrator/Architect, 2 Builders, 1 Product Owner. One delivery unit, full-stack by default.
  • Two parallel workstreams, load-balanced. 1–5 day ship cycles. No sprint ceremonies imposed on you.
  • Fixed monthly rate ($66K–$95K). 6-month minimum. Single-outcome trials available.
  • Optional outcome alignment: bonus on agreed metrics, partial-refund on Day-90 thresholds.

"I want a unit that ships, not a team I have to run."

Read the Pod model →
MANAGED CAPACITY

Scale

Predictable delivery capacity for a long run. Same people, your roadmap, your stack. After 90 days the team operates like an internal function.

  • Managed team, sized to your roadmap. We run the rhythm: sprints, releases, quality.
  • Lowest blended rate of any continuous model. Long commitment lets us load-balance utilization.
  • Same people month over month. Context compounds, edge cases get learned.

"I know what I need. Give me a team that operates like mine."

12+ monthsManaged teamBlended rate
VARIABLE CAPACITY

Flex

Augment your team with the composition you need, reshape as the work changes. Maximum control: you direct individuals day-to-day.

  • You pick roles and seniority mix. We supply, vet, and replace.
  • Embedded in your process, your tools, your ceremonies. You manage day-to-day.
  • Higher per-hour rate than Scale. Flexibility has a price.

"I'll run it. You supply the people."

3–12 monthsManaged talentReshape on demand

Pick by what you're buying

OutcomeAI PODScaleFlex
What you buyA resultA delivery unitA managed teamPeople
Who runs deliveryAquivaAquivaAquivaYou
Who owns scopeLocked upfrontYou (roadmap)YouYou
CommitmentProject length6+ months12+ months3–12 months
Pricing shapeFixed totalFlat monthlyBlended monthlyPer-role rate
CadenceMilestones1–5 day cyclesSprintsYour ceremonies
Best forDefined deliverableAI-leveraged buildsLong-run roadmapVariable staffing

Outcome

What you buy
A result
Who runs delivery
Aquiva
Who owns scope
Locked upfront
Commitment
Project length
Pricing shape
Fixed total
Cadence
Milestones
Best for
Defined deliverable

AI POD

What you buy
A delivery unit
Who runs delivery
Aquiva
Who owns scope
You (roadmap)
Commitment
6+ months
Pricing shape
Flat monthly
Cadence
1–5 day cycles
Best for
AI-leveraged builds

Scale

What you buy
A managed team
Who runs delivery
Aquiva
Who owns scope
You
Commitment
12+ months
Pricing shape
Blended monthly
Cadence
Sprints
Best for
Long-run roadmap

Flex

What you buy
People
Who runs delivery
You
Who owns scope
You
Commitment
3–12 months
Pricing shape
Per-role rate
Cadence
Your ceremonies
Best for
Variable staffing

Two other shapes are available when they fit: Surge (Specialist burst, as-needed. A senior architect or specialist for a defined window (weeks, not months). Premium rate, no long-term commitment) and Sustain (Managed services and ops. SLA-backed, always-on team handling incidents, releases, and platform health post-go-live). Ask if either fits the work better than the tracks above.

Chapter 03 · Operate

Operating is where outcomes compound.

Software that ships but doesn't get used isn't software yet. Operate is where you earn adoption, where each cycle gets cheaper, and where most consulting engagements stop trying. We don't.

Step 01

Enablement

Training, docs, change management. So adoption doesn’t stall at the login screen.

Step 02

Adoption

Track usage, surface friction, close the gap between "deployed" and "actually used."

Step 03

Optimization

Tune performance, cut cost, sharpen accuracy. Each cycle is a measurable improvement.

Step 04

Insight

Production data shows where the next high-value bet is.

Step 05

Compound

Use what you learned to prioritize the next build. Each cycle makes the next one cheaper and faster.

Numbers we move

Numbers you can audit.

A fixed-rate engagement only works if you can see how delivery is performing. Transparency comes built into the model. You see the same data we use to run the work.

The numbers are how we keep ourselves honest. We share the same dashboards we'd want to see if we were the customer, including the metrics that make us look bad early.

87%
Pilots reach production
<90d
To live agent
~7%
Pod overhead vs. ~15–25% on traditional capacity teams
4.95/5
CSAT across engagements
7+
Internal AI products in production
$130K+
License spend retired

Industry comparison drawn from Hypersense's 2025 software-development effort-allocation study (10–20% PM allocation) and APQC (~25% knowledge-worker productivity drains).

Per engagement, we report cycle velocity, defect escape rate, adoption curves, and the business-outcome delta against your baseline. Monthly. Against thresholds we agreed in the SOW. If indicators slip at Day 60, we restructure then. Not Day 90.

Next step

Let's start building!

Most engagements start with a 30-minute call about where you are and what's blocking the next move. We don't bring a deck.

Read the Pod model