Stack audit & value map
Every tool classified with contract, users, value and renewal date.
Consulting engagement
MarTech & AI enablement - rationalise the stack, govern the AI layer, ship faster.
Most marketing stacks have tripled in five years - and the ROI has not followed. Npexpos helps you consolidate, integrate and introduce AI where it actually moves work forward, not just adds cost.
Why Npexpos for MarTech & AI?
We design stacks that marketers can operate, finance can fund and IT can approve - with an AI layer that has explicit guardrails, not a scattered collection of SaaS add-ons.
Consolidation before expansion
Most stacks need fewer tools - not more. We find duplication, retire shelfware and free budget before introducing anything new.
Data contracts as the backbone
A warehouse-centric model, reverse ETL, and event contracts so every tool speaks the same customer language.
AI with guardrails
Use cases with clear human review, evaluation and rollback - so AI accelerates work without introducing silent risk.
Change IT will approve
Security, privacy, SSO, data residency and procurement discipline baked in, not added later.
Outcomes Npexpos clients measure
Illustrative ranges - swap with your verified metrics when deployed.
20-40%
Net reduction in MarTech licence spend after consolidation
2-3x
Faster campaign cycle time via AI-assisted production
8
Phases with engineering-ready artefacts and owners
The MarTech & AI engagement - in 8 phases
A pragmatic path from stack sprawl to an operating platform.
Stack audit & value map
Every tool catalogued: contract, spend, active users, integration depth and business outcome. Shelfware becomes visible.
Target architecture
The desired architecture with a warehouse core, event contracts and a canonical customer record - designed with IT and data.
Consolidation & retirement plan
Which tools to keep, renegotiate, retire or replace, sequenced against renewal dates and migration effort.
Integration & data contracts
Event specs, reverse ETL flows, identity resolution and consent propagation - the glue.
AI use-case portfolio
A ranked list of AI use cases - from brief generation and QA to segment discovery and creator matching - each with review, evaluation and rollback plans.
AI governance & evaluation
Model choice, data boundaries, prompt management, human review and measurable evaluations so AI rollout is auditable.
Operating model & ownership
Who owns which surface, change-control, intake process and a MarTech council that meets monthly - not a one-off decision.
Enablement & handover
Playbook, training and a 12-month roadmap so your in-house team can run the platform after handover.
What you receive
Target architecture blueprint
Warehouse-centric model with integration contracts and identity resolution.
AI use-case portfolio
Ranked, scoped use cases with evaluation plans - so AI rollout is auditable.
Operating model & roadmap
Ownership, change-control, intake and a 12-month delivery plan.
Frequently asked questions
Are you tied to any vendors?
No. We design against your problem; our recommendations are not affiliated with resellers, implementers or referral fees.
Do you implement, or only advise?
We advise and oversee. Implementation is done by your engineering team, your SI, or a partner we help you select.
How do you handle AI safety, privacy and data residency?
Data boundaries, prompt controls, PII handling, region-locked infrastructure and human review for every use case with real-world impact.
Can you help us build a CDP in the warehouse?
Yes - warehouse-centric identity, event contracts and reverse ETL is our default recommended pattern for most clients.
Do you evaluate AI vendor claims?
Yes. We run structured evaluations on pilot data and compare against your current baseline - not against the vendor's own demos.
How long is a typical engagement?
Diagnostics: 3-5 weeks. Rationalisation programme: 12-20 weeks. Advisory retainer: 6-12 months.