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We build the data foundation first, then put AI to work on it.

We work with your team so leaders decide from one set of numbers everyone trusts. Then AI takes routine work off people's desks and speeds up daily operations, with a person approving what matters.

Snowflake Premier & Select PartnerSnowPro-certified team

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Data + AI initiatives usually break down at one of three points.

Each point has a different underlying issue and calls for a different first step. Which one looks most like your organization?

  1. 01Vision → Foundation

    ERPCRMDocsSheetsGoldSilverBronzeAISourcesGoverned layerAI use cases

    The AI ambition is ahead of the data foundation.

    The roadmap and use cases exist, but the data AI needs is still spread across ERP, CRM, documents and spreadsheets.

    What gets in the way

    • Disconnected source systems
    • Inconsistent business definitions
    • Security not designed for AI access
    7 weeksto a governed, real-time data foundation for a university group with 20,000+ studentsRead the case

    Usually starts with Full transformation

  2. 02Foundation → Intelligence

    Q3 marginby region?Semantic layerData foundationSourceQuestionSemantic layer + AICited answer

    The data foundation is in place, and the way people work has barely changed.

    Teams still search, reconcile numbers and build reports by hand. The next step is intelligence people can query directly.

    What this adds

    • Natural-language access to data
    • A semantic layer with business context
    • AI search and RAG over documents
    60% → 95%claims-document classification accuracy for an insurance processorRead the case

    Usually starts with Agentic engineering

  3. 03Intelligence → Operations

    PDFAgentMCPERP · CRMRequestAgentApprovalSystem of record

    The AI works in a demo and is still outside daily operations.

    Production workflows cross applications and depend on permissions, rules, approvals and human judgment. Getting there takes engineering around the model.

    What production AI needs

    • Agent orchestration
    • Human approval controls
    • Evaluations and observability
    15–19 hrsof administrative time back every week at Magnolia DoorsRead the case

    Usually starts with Agentic engineering

Two practical starting points

The first step can be small: start with a readiness session, or bring one workflow and we map how Data + AI could improve it.

Data + AI readiness session

We assess the current environment across data, architecture, governance, AI, security, integration and operational readiness. The session delivers a practical picture of what is ready today, what needs work, and where the highest-value opportunities are.

Deliverables

  • Current-state assessment
  • Key technical and operational gaps
  • Data foundation architecture considerations
  • AI opportunities tied to the environment
  • Recommended priorities
  • Practical next steps

Map one workflow with us

Bring one process that takes too much time, needs heavy manual coordination or depends on institutional knowledge. We map the systems, data, decisions, documents and people involved, then outline how the data foundation and Claude could support or automate it.

Deliverables

  • The workflow mapped from trigger to outcome
  • Required data sources
  • Integration requirements
  • A data + AI architecture
  • Automation opportunities
  • A feasibility assessment
  • A recommended next step

Results from client engagements

View case studies
Magnolia Doors

Manufacturing · San Antonio, TX

Installation scheduling from 17 hours a week to under two

15–19 hrs
Administrative time back every week
~3 min
Was 23 to 35 minutes per installation
Read the case study
Manufacturing: Installation scheduling from 17 hours a week to under two
Story 1 of 2: Installation scheduling from 17 hours a week to under two
HussmannLendzDifrenosa

Recognized by Snowflake

Viewnear was one of 41 partners, from a network of more than 14,000, that Snowflake named on its CoCo Global Partner Momentum wall at Summit 2026.

Snowflake's CoCo Global Partner Momentum wall at Summit 2026, listing 41 partner logos including Viewnear, in front of a keynote audience
The wall on stage, with Viewnear in the bottom row.

CRNQuoted in CRN, 3 storiesRead the coverage

  • Snowflake Premier Partner badge

    Premier & Select Services Partner

    The Premier and Select services-partner tiers of the Snowflake Partner Network, held across the USA and LATAM.

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  • Snowflake CoCo Preferred Partner badge

    CoCo Preferred Partner

    CoCo is Snowflake's own coding agent. The Preferred program names the partners building with it.

  • SnowPro Core certification badge

    SnowPro-certified team

    Architects and engineers certified by Snowflake. They build data foundations and the Cortex AI layer that runs on them.

Three ways to work with us

Advisory and agentic engineering for teams that already have part of the work in hand, and a full transformation when the data foundation and the agents both need to be built.

01Data + AI advisory

We find where data and AI pay off first, and plan the build with your team.

  • Workshops and an operations diagnosis
  • Readiness assessment, with the KPIs to track
  • Use cases ranked by value, and an architecture blueprint

02Agentic engineering

When the use case is clear, we engineer the agents inside your environment, on your data.

  • Agent architecture on governed data
  • Workflow design with approval points
  • Engineering, evaluation and deployment
Claude Certified Services Partner badge

Claude Certified Services Partner15+ Claude Certified Architects on the team

01 + 02Full transformation

From scattered data to agents running in daily operations, with the data foundation built first.

  • A delivery lead, an architect and certified engineers, embedded on US business hours
  • Everything in 01 and 02, plus the data foundation
  • Go-live, then run by your team or by Viewnear as a managed service

What each engagement covers

  • AI readiness assessment01
  • Use-case discovery and ROI ranking01
  • Architecture blueprint01
  • Technical advisory01
  • RAG systems02
  • Document intelligence02
  • Custom AI agents02
  • Multi-agent workflows02
  • Claude and MCP integrations02
  • Evaluations and LLMOps02
  • Data foundation build01 + 02
  • Managed service01 + 02

Each engagement can run as a fixed-cost build, time and materials or a dedicated team, and the build can continue as a managed service.How pricing worksHow an engagement runs

Our team is already in place, so the work starts right after discovery.

A nearshore team of data and AI architects and engineers in Monterrey, Mexico and Austin, Texas, working on Central Time during your business day. The budget goes straight into use-case sprints.

Work at Viewnear

We are data and AI architects, engineers and delivery leads, working from Austin and Monterrey for clients across the USA and LATAM.

Senior Data & AI Engineer

Full-time · Remote (USA, LATAM)

Design and build data and AI solutions on Snowflake for enterprise clients, from pipelines and data models to AI use cases running in production.

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