ELEVATE: AI-Native Outcome-Based Engagement Model
Built for enterprises modernizing platforms, scaling AI, & operating under pressure to
lower cost-to-serve while increasing velocity & reliability.
TechBlocks ELEVATE replaces time-and-materials delivery with AI-orchestrated, outcome-indexed capacity. If KPIs don’t move, our economics don’t either.
AI has fundamentally changed delivery speed. Time-and-materials hasn’t kept up. The result is a structural failure: as cycles compress, time-based services become economically misaligned & unsustainable.
In the traditional model, vendors win when hours increase, not when outcomes improve. AI-driven efficiency and automation erode billable hours and shrink revenue. That incentive gap penalizes speed, turns innovation into a cost, and keeps cost-to-serve high because the economics reward effort, not impact.
ELEVATE fixes the misalignment with a KPI-driven model where:
- Capacity is powered by AI and global delivery pods
- Success is defined by measurable KPI movement, not days worked
- Incentives finally align around speed, quality, and efficiency
ELEVATE is anchored to six contractually baselined metrics
1. Cost-to-serve
Measured as cost per order, ticket, customer, or platform. Typical impact is a 20–40% reduction over 12–24 months.
2. Delivery velocity
Measured as releases per month and lead time for change. Typical impact is 2–3× faster releases and 10–30% shorter cycles.
3. Reliability & Uptime
Measured as uptime %, MTTR, and incident rate. Typical impact is 99.9%+ stability across critical platforms.
4. Quality & Defects
Measured as defects per release, escaped defects, and rework. Typical impact is a 30–50% reduction in production defects.
5. AI Adoption
Measured as % of AI-assisted workflows and active AI users. Typical impact is 30–60% AI adoption in scoped workflows.
6. Cloud & Operational Efficiency
Measured as cloud spend per transaction and idle capacity. Typical impact is a 10–25% reduction in cloud spend and scope.
ELEVATE combines three TechBlocks capabilities into a single delivery & commercial model with clear accountability
AI-Accelerated
Software Factory
An AI-native SDLC where agents execute the heavy lifting and humans govern the control points.
What it delivers:
- Agent-accelerated planning, build, test, and DevSecOps
- Standardized, reusable delivery flows
- Human-in-the-loop oversight for architecture, security, and releases
Measured impact:
- 2–3× velocity
- 30–50% fewer defects
- Improved deployment success rates
VRO
Value Realization Office (VRO) is the joint governance layer that treats value as a first-class deliverable.
What it does:
- Baselines KPI performance upfront
- Sets quarterly targets and weekly telemetry
- Runs variance analysis and course-corrects in real time
What you get:
- A live value scorecard
- Clear attribution from initiatives to KPI movement
- Decisions driven by data, not optimism
Shared-Success Model
A commercial pricing structure where fees move with your KPI performance, not with time spent.
How it works:
- Base fee for core platform and delivery capacity
- Variable fees indexed to outcomes (cost, velocity, quality, AI adoption)
- Risk-sharing bands with upside and downside protection
Result:
Our incentives move with your P&L, aligning both sides around measurable outcomes and results.
ELEVATE in action
A leading North American retailer engaged TechBlocks to modernize its digital platform and operationalize AI across delivery. The goal was to cut engineering cost-to-serve, increase release velocity, and protect peak-season uptime, with shared-success economics tied directly to measurable KPI movement.
Baseline
- Release cadence: 1 major release every 6–8 weeks
- High engineering cost-to-serve
- Peak-season reliability risk
Targets
- 25–30% cost-to-serve reduction
- 2× release cadence
- 99.9%+ uptime
Results
- 30–40% cost-to-serve reduction
- 2× faster release cycles
- 99.9%+ production stability during peak
- Variable fees indexed directly to KPI over-performance
The ELEVATE Engagement Lifecycle
Phase 0
Baseline & Design
4–6 weeks
- Measure current KPI baselines
- Select 2–3 high-impact value streams
- Design AI-Accelerated Software Factory flows and governance
- Define outcome targets and commercial bands
Phase 1
Prove & Stabilize
3–6 months
- Deploy AI-Accelerated Software Factory delivery
- Introduce agents into agreed SDLC stages
- Achieve initial KPI deltas (e.g., 10–15% cost reduction, 50–80% velocity uplift)
Phase 2
Scale & Deepen
6–18 months
- Expand across products, regions, and teams
- Increase AI automation depth and agent coverage
- Drive 20–40% cost-to-serve reduction and 2–3× velocity
Phase 3
Institutionalize
18–36 months
- Embed ELEVATE into your GCC and operating model
- Co-run VRO and AI-Accelerated Software Factory with internal leaders
- Make outcome-based delivery the default, not the exception
ELEVATE is designed for enterprises that need hard ROI & operate where uptime, security, & compliance are non-negotiable. If you’re modernizing core platforms, scaling AI beyond pilots, or want a partner contractually accountable for outcomes, let’s talk. We’ll baseline your KPIs & turn them into a practical 90-day roadmap.
Expertise you can trust
“With TechBlocks we found a partner who continuously went above and beyond. They were able to translate our business priorities into a cohesive solution and were able to roll with all the ups and down on our side. Their focus on our needs and the way they collaborated with our various user groups has been exceptional.”
Veresh Sita, CDO, Technology/Marketing/Insights – Colliers International
Global Professional Services & Investment Management Company.
Ready to move delivery from hours to outcomes?
Talk to an ELEVATE advisor today about your KPI baselines and targets, and let’s explore what’s possible.
