A POC-first model built for
enterprise procurement.
Most AI vendors sell you a platform and hope. We sell you a POC against signed KPIs — and only if it hits, we build. Seven engagement models, one ethos: outcomes before invoices.
Four phases. Four to twelve weeks to value.
A predictable path from first conversation to production, with go/no-go gates at every phase. No phase lasts longer than it needs to.
Discover
Walk in with a hunch. Walk out with a sized ROI model, an architecture your CTO will sign, and a POC scope your CFO can approve.
Prove
Validated business case on real data, against signed KPIs. Fixed-fee. Either it clears your numbers — or you keep the architecture blueprint and walk away.
Scale
Production system in your perimeter. Deployed models, APIs, dashboards, and ML Ops — handed over to your team to own.
Operate
Managed services with drift detection, retraining, and performance SLAs. Pay against the metric you care about, not against headcount or hours.
Seven ways to engage. All auditable.
Every model has fixed deliverables, a defined duration, and a pricing structure that enterprise procurement can approve. Pick the one that matches where you are — or start with a POC and migrate as you scale.
Consulting & Advisory
AI readiness assessment, due diligence, use-case prioritization, ROI analysis, roadmap.
Early-stage clients exploring AI transformation.
POC / Pilot Mode
Prototype / working model, business impact metrics, success criteria.
Clients testing value of document automation, voice analytics, or predictive models.
Project-Based Delivery
Deployed models, APIs, dashboards, documentation.
Well-scoped AI solutions — visual inspection, chatbots, sentiment analysis.
Managed Services
Model performance monitoring, drift management, updates.
Enterprises running production AI systems.
Value / Outcome-Based
Defined performance metrics, continuous measurement.
Mature clients confident in measurable ROI.
Staff Augmentation
Data scientists, MLOps engineers, annotators on demand.
Large organizations needing flexibility and scalability.
Platform-as-a-Service
Multi-tenant access to the TerraEdge AI Framework — Doc-In-Sights, Voice Insights, ConverseAR — on pay-per-use economics.
Teams with steady volume but without the appetite to run their own ML Ops.
Outcome pricing. Not story pricing.
We don't sell story points, or seats, or undifferentiated hours. We price against the metric that matters — accuracy gained, volume processed, cost displaced.
Fixed fee against KPIs. Conversion credit on scale.
Milestone-based billing or outcome share. Your choice.
Monthly retainer with performance SLAs. Transparent drift reports.
Base + performance incentive. Reserved for clients with clean baselines.
What procurement actually asks.
Cost, payback, ownership, what-if-it-fails, perimeter, and data residency — the six questions every CFO and CIO brings to the conversation.
What does a typical TerraEdge engagement cost?
Who owns the AI you build with us?
What happens if the POC doesn't clear KPIs?
Can the system run inside our perimeter — on-prem or air-gapped?
Not ready for AI yet? Want to chat about possibilities?
No pitch, no pressure. Just a conversation about where AI could fit, or where it can wait. Bring your skepticism — we'll bring ours.
Tell us the metric. We'll tell you the POC.
Six fields, one conversation. If we can define a KPI we both believe in, we'll scope a 4–12 week POC in under a week.