Our approach
Delivery you can govern.
A proven Snowflake methodology, plus the governance that de-risks the engagement itself, so the buy is as low-risk as the outcome is high.
How we deliver and keep delivering
A six-step loop, not a one-way project. We work one priority use case at a time, taking each from discovery to governed, Cortex-powered data in production on Snowflake, then start the next. Your governed, AI-ready data grows with your business as we keep delivering.
- 1
Discover
Assess the current estate, data sources, and business goals; define success metrics.
- 2
Design
Architect the target Snowflake platform, governance model, and semantic layer.
- 3
Migrate & Ingest
Move and connect data with automated translation, validation, and Openflow pipelines.
- 4
Build
Engineer data products, analytics, and Cortex AI / agentic workloads on governed data.
- 5
Govern & Validate
Apply Horizon Catalog lineage, access controls, and PII classification, plus Horizon Context so every team and AI agent shares one trusted business context; test for trust.
- 6
Run & Optimize
Operate, monitor, and tune consumption and performance, with enablement for your team.
Why it works
A partner who knows the whole journey
The whole modern data stack, not one tool
Ingestion (Openflow, Snowpipe Streaming), transformation (dbt, Snowpark, Dynamic Tables), governance (Horizon Catalog and Horizon Context), analytics (Snowsight, Streamlit), and AI agents (Cortex, Snowflake CoWork), all centered on your governed Snowflake core.
Governed and open by design
Built on Apache Iceberg and Open Catalog (Polaris) so your data stays interoperable across engines and clouds: no vendor lock-in.
Get it right the first time
Proven migration frameworks and certified architects reduce risk and rework when you move off Teradata, Oracle, Hadoop, or SQL Server.
Beyond dashboards to data agents
We ground Snowflake CoWork (the personal AI agent) and Cortex Agents in your governed Semantic Views and Horizon Context, so business users get cited, trustworthy answers from the same definitions every team uses.
How engagements run
De-risked, start to finish
Clear timelines, steering, and a clean hand-over: the questions every sponsor asks, answered up front.
A fixed 8–16 week arc
Most initial platforms reach production in 8–16 weeks, scoped to your data and use cases, with value delivered from the first sprint.
Steering & transparency
Regular steering reviews, a shared backlog, and clear decision gates keep sponsors in control of scope, budget, and priorities throughout.
De-risked by design
We prove the approach with a focused proof of concept before the full build, so you commit to scale on evidence, not a slide deck.
Built to hand over
Documentation, enablement, and a transition plan in every engagement, so your team runs and extends the work confidently.
Business impact
What changes, and when
A practical view of the value an engagement returns, by horizon, not by feature list.
Foundations & first value
A governed Snowflake foundation stood up, priority data flowing, and the first production dashboards live.
Scale & self-service
Analytics and AI use cases rolled out across teams; self-service adopted and manual reporting retired.
Compounding advantage
New use cases shipped in weeks, run cost tuned, and a team fluent enough to keep extending it on their own.
Proof
How it plays out in practice
From hand-sorted documents to 95% accurate claims classification in seconds
A claims processing company was sorting documents from many insurance providers by hand, causing delays, errors, and lost files. Using Snowflake Cortex AI functions like AI_EXTRACT, Viewnear automated classification and data extraction, lifting accuracy from 60% to 95% and cutting per-document handling to four seconds.
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Real-time insight into 20,000+ students across campuses, live in seven weeks
A group of universities serving 20,000+ students across Miami and Latin America had academic records and LMS learning events siloed across campuses. Viewnear built a governed, real-time student data pipeline on Snowflake: a governed environment, native Blackboard Data Share integration, and real-time Caliper event streaming, unifying academic and learning-activity data into one governed source.
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One trusted golden record across eight business domains
A commercial-vehicle dealer group ran sales, service, parts, and the back office on separate systems, with no single version of a customer, vehicle, part, or supplier. Viewnear built a corporate master data foundation on Snowflake: a progressive multi-source golden record across eight business domains, using a Medallion architecture, Openflow ingestion, dbt transformations, and per-domain Snowflake CoWork agents.
Read moreLet's make Snowflake do more.
Tell us where you are (migrating, scaling, or building AI) and we'll map the fastest path to value.