What Is TechBlocks ELEVATE?

TechBlocks ELEVATE is a commercial and delivery model in which fees are indexed to measurable business outcomes rather than hours worked. Capacity is supplied through AI-augmented delivery pods instead of incremental headcount, and the commercial terms move in step with a fixed set of contractually agreed KPIs; a metric that stays flat against its baseline simply doesn’t trigger the variable portion of the fee.

The model exists to correct a specific misalignment that AI has exposed in conventional technology services contracts. Under time-and-materials pricing, a vendor’s revenue grows with hours billed. AI-driven automation now lets the same work get done in fewer hours, which means a vendor billing by the hour is financially penalized for becoming faster. ELEVATE removes that conflict by pricing the engagement against the result delivered, not the effort spent producing it.

Why ELEVATE Replaces Time-and-Materials Delivery

Time-and-materials contracts were built for an era when output scaled roughly with hours worked. AI breaks that assumption: a team using AI-assisted delivery can ship the same feature in a fraction of the time, but a T&M contract has no mechanism to reward that — it simply reduces the bill. This creates a structural disincentive for vendors to adopt AI aggressively, even when doing so would benefit the client. ELEVATE addresses this by decoupling the fee structure from hours entirely and tying it instead to outcomes the client actually cares about, so faster delivery and lower cost-to-serve work in the vendor’s financial interest as well as the client’s.

The Six Metrics Behind TechBlocks ELEVATE

ELEVATE engagements are baselined against six metrics, agreed contractually before delivery begins:

Cost-to-serve, tracked per order, ticket, customer, or platform, with engagements generally landing a 20–40% drop across 12–24 months.
Delivery velocity, based on monthly release counts and lead time for change, where 2–3x faster shipping is a common outcome.
Reliability and uptime, covering uptime percentage, recovery time, and incident frequency, with critical platforms usually holding above 99.9%.
Quality and defect rates, looking at defects per release and escaped issues, where production defects tend to fall 30–50%.
AI adoption, measured by the proportion of workflows running through AI assistance, with scoped functions usually reaching 30–60% uptake.
Cloud and operational efficiency, tracked through spend per transaction and idle capacity, generally trimmed by 10–25%.

Each metric is measured against a pre-engagement baseline, not an industry benchmark, which is what allows the commercial terms to reference them directly.

Core Components of the ELEVATE Model

ELEVATE is built from three components that operate together rather than independently:

AI-Accelerated Software Factory — an AI-native software delivery process where AI agents handle execution-heavy work across planning, build, and test, while engineers retain control over architecture, security, and release decisions.
VRO (Value Realization Office) — a shared tracking function, staffed by both TechBlocks and the client, that checks the six baselined metrics every week and opens a variance review the moment a number drifts off plan.
Shared-Success Model — the commercial structure underneath ELEVATE, combining a base fee for delivery capacity with a separate component that rises or falls based on how the six metrics actually land, inside risk bands that work in both directions.

How the ELEVATE Engagement Lifecycle Works

ELEVATE engagements progress through four phases:

Phase 0 — Baseline and Design (4–6 weeks). The starting KPI numbers get measured, a small set of high-impact value streams gets chosen to pilot the model, and the outcome targets and fee terms get written into the contract.
Phase 1 — Prove and Stabilize (3–6 months). The AI-Accelerated Software Factory goes live inside a defined set of SDLC stages, and the first measurable movement against baseline shows up.
Phase 2 — Scale and Deepen (6–18 months). Coverage broadens to additional products, regions, and teams, with automation reaching deeper into the workflow at each stage.
Phase 3 — Institutionalize (18–36 months). VRO and the Software Factory move under the client’s own leadership to run day-to-day, and outcome-based delivery becomes the standard way the engagement operates rather than a parallel initiative.

ELEVATE vs. Traditional Time-and-Materials Contracts

Time-and-materials contracts price delivery by hours worked, which means efficiency gains from AI reduce vendor revenue rather than rewarding it.
Fixed-bid contracts price delivery by scope, which discourages flexibility once requirements shift mid-engagement.
ELEVATE prices delivery by KPI movement against a contractual baseline, which aligns vendor revenue with the client’s actual operating improvement regardless of how many hours that improvement took to deliver.

Business Outcomes of the ELEVATE Model

Commercial terms that reward speed and efficiency instead of penalizing them.
A documented, weekly-tracked link between specific initiatives and the KPI movement they produce.
Reduced cost-to-serve and faster release cycles without a separate cost-reduction initiative running in parallel.
Shared financial exposure between client and vendor, rather than the vendor being paid regardless of outcome.