Data & AI Services for AI-Ready Enterprise Data
SolvIT AI's data and AI services get your data ready for AI: we audit data quality, set governance rules, and clean and integrate scattered sources into a single source of truth your AI agents and analytics can trust. We apply NASA and IBM methodologies to turn fragmented data into mission-critical intelligence.
Build on a Foundation of Integrity
Most AI projects fail not because of the model, but because of the data. Fragmented pipelines and inconsistent governance create "hallucinations" and operational risk.
Leveraging 20+ years of experience with NASA/JPL and IBM Global Services, we bring mission-critical data standards to your business. We connect scattered sources—from CRMs to proprietary databases—to architect a secure "Single Source of Truth."
Data work is the first phase of our AI services: it feeds AI strategy and roadmaps and the managed AI-Ops that keep models reliable in production. See it in practice in our invoice automation case study.
Enterprise Data Intelligence:
- ✓ Unified Data Pipeline Architecture
- ✓ NASA-Grade Governance & Compliance
- ✓ IBM-Standard Data Integrity Audits
- ✓ Predictive Sales & Trend Analytics
- ✓ Automated Data Quality Assurance
Data & AI Services FAQ
What do SolvIT AI's data and AI services include?
Data integrity audits, governance and compliance frameworks, data cleaning, unified pipeline architecture that connects CRMs and proprietary databases into a single source of truth, automated data quality assurance, and predictive sales and trend analytics built on that cleaned data.
How is SolvIT AI different from other data and AI service firms?
We fix the data foundation before building models. Our methods come from 20+ years of work with NASA/JPL and IBM Global Services, and we focus on mid-market and enterprise teams that need AI running on verified data rather than a slide deck.
What are NASA-grade data standards?
These are rigorous validation and verification protocols designed to ensure data reliability in high-stakes environments where "near-zero" error rates are the requirement, not the goal.
How does governance prevent AI hallucinations?
By implementing strict data cleaning pipelines and semantic guardrails, we ensure your AI agents only reference verified, high-fidelity data sources during the reasoning process.
Where should we start if our data is a mess?
Start with a diagnostic: take the free AI readiness assessment, then we audit your sources, rank data quality issues by business impact, and set governance rules before any AI build begins. Our guide “My data is a mess” walks through the first steps.
Related reading
Phase I: Diagnostic data governance · Data governance pitfalls · AI readiness checklist · Case studies · Talk to us