Cost signal - Gartner
~12.9M$
Average annual loss per organisation from poor data quality.
Gartner Research
Why this matters
The edge does not come from AI alone. It comes from the way your data and workflows make AI trustworthy.
Why start with data
AI doesn't fix operational chaos. It multiplies it.
Nexavenu starts before AI. We assess whether the business captures the right data, how clean and trusted it is, which workflows generate it, and what behaviours must change so technology multiplies performance, not noise.
Advisory lens
The problem is not just data quality. It is the operating environment that creates that quality.
What this means
Bad data is not a reporting problem. It is an operating-model problem. If the workflows are broken, AI simply scales the defect faster.
Data Monetisation Methodology by Nexavenu
Advisory, Ethics, Governance
0
Data
Nexavenu recognises the value of data governance — without it, data rapidly loses its reliability, creating missed opportunities and wasted resources. We assess what data exists, what is missing, what it costs, and whether it supports your business objectives, then clean, govern, and reassess continuously so data becomes a genuine competitive advantage.
1
Operational Excellence & Governance
Our consultants assist your business with process engineering and governance to maximise results and minimise risk. We re-engineer workflows, standardise operations, improve data capture, and align people around the operating model — ensuring your business runs efficiently and your governance framework scales with you.
2+
AI Momentum & Ethics
We are aware of the risks that come with AI. Using Agentforce, we ensure agents are built to stringent rules preventing hallucinations, data leaks, and privacy violations. We adopt AI, automation, and analytics as a multiplier layer only once data and operations are trusted enough to scale — adhering to Salesforce ethical guidelines throughout.
∞
Flywheel Effect & Advisory
Our team understands your business and industry. Each AI agent is tailor-made to your organisation, aligned with your goals and objectives. We measure outcomes, behaviours, data quality, and adoption so every improvement feeds the next cycle of operational intelligence — extracting the full potential of Agentforce.
The trusted data flywheel
Phase 0 — Data foundation & IP continuity
Walk backwards from business objectives
Identify the data, behaviours, workflows, and decision points needed to achieve strategic outcomes.
Re-engineer how data is created
Improve processes so better data is captured naturally through the way people work.
Centralise IP and operational knowledge
Protect continuity when people join, leave, or move roles by embedding know-how into systems, workflows, governance, and AI copilots.
Databricks Integration
The analytical power
of Databricks meets
Salesforce Data Cloud
Databricks
+
Data Cloud
Nexavenu bridges the Databricks Lakehouse — ML, Unity Catalog, Delta Lake — with Salesforce Data Cloud unified profiles to create real-time, trusted, scalable customer intelligence.
Unity Catalog — Unified governance
Centralised data governance, lineage, and access control across the Lakehouse, aligned with your Data Cloud policies.
Delta Lake — Reliability at scale
ACID transactions, time travel, and guaranteed data quality to feed AI with data you can trust.
MLflow & AutoML — Accelerate AI
Experiment tracking, model lifecycle management, and production deployment — directly connected to Agentforce for contextual AI.
Zero-Copy Integration with Salesforce
Bi-directional data sharing without duplication via native connectors — reducing cost and latency, maximising data freshness.
The trusted data foundation
How INFA fits into the Salesforce product bagTrusted Data
Foundation
= AI at Scale
= AI at Scale
Salesforce ecosystem
MuleSoft
Moves and orchestrates data
Informatica
Prepares and governs data
Data Cloud
Activates data inside Salesforce
Agentforce
AI agents on trusted data
MuleSoft
Moves and orchestrates dataConnects and orchestrates data flows across ERP, CRM, and cloud platforms without breaking operating continuity.
Informatica
Prepares and governs dataGoverns, cleanses, and certifies enterprise data quality before it feeds Salesforce or AI models.
Data Cloud
Activates data inside SalesforceUnifies profiles and signals in real time to activate trusted contextual intelligence inside Salesforce.
Agentforce
AI agents on trusted dataDeploys AI agents that act on certified data for service, sales, and execution at scale.
Built on industry leaders
Phase 2+ — The technology multiplier ecosystem
Salesforce - Customer workflows
MuleSoft - Integration fabric
Data Cloud - Unified profiles
Agentforce - AI execution
Databricks - ML & analytics
Informatica - Data quality
Azure - Enterprise data
Claude - AI IntegrationSalesforce - Customer workflowsMuleSoft - Integration fabricData Cloud - Unified profilesAgentforce - AI executionDatabricks - ML & analyticsInformatica - Data qualityAzure - Enterprise dataClaude - AI IntegrationWhat is your top 1 or 2 metric
to improve in 3 months?
Let's go→Choose your entry point
Accelerator
Best for a focused business unit that needs to understand data quality, fix core workflows, and build an AI-ready operational baseline.
- AI readiness and data quality assessment
- Business process review and quick-win redesign
- Data cleansing, trust scoring, and dashboard baseline
- One AI-ready operational excellence use case
Transformation
Best for enterprise teams needing a repeatable operating model across data, operational excellence, people adoption, and AI momentum.
- Operating model and governance framework
- Enterprise process re-engineering roadmap
- Data Cloud and integration architecture blueprint
- AI adoption, behavioural change, and continuity model
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