Our approach
Delivery leaders can govern.
Use-case-driven sprints with working software at every demo, plus the governance that de-risks the engagement itself, so sponsors always know where the work stands.
The experience
What an engagement feels like from the sponsor's seat
The reviews the sponsor runs, the demos the team watches, and the decisions that stay in-house: one engagement, from the first scoping session to handover.
Week 1–2: a scope worth signing
It starts with a paid discovery: our architects sit with the stakeholders, walk the sources, and rank the use cases by what they return. The sponsor comes out holding a fixed scope at a fixed price, so what goes upstairs to the board is a commitment, not an estimate.
The sprint rhythm
Then the cadence sets in: every sprint closes with a sprint demo of something that works against real data, not a status deck. Something usable ships each time, so progress is a thing the team can click, not a percentage anyone is asked to believe.
Week 3 feels like this
The sponsor sits in the first steering review, reordering a shared backlog that is genuinely theirs to reorder, with a decision gate ahead that waits on the business, not on us. Scope, budget, and priorities stay in-house the whole way through.
Proof before scale
Before the full build, a focused proof of concept has to earn the go-ahead on real data and the hardest use case. The decision to scale rests on evidence the team watched happen, never on a slide.
The parallel truth
When the first dashboards go live, a parallel run checks them against the numbers teams trust today, and every mismatch gets chased down and explained. The new figures earn their standing by reconciling, not because we vouched for them.
Handover, documented
The build ships with runbooks, documentation, and enablement sessions, plus a transition plan that names who runs what when we step back. Most engagements reach first value in 8–16 weeks, and from there the team extends the work on its own terms.
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. The governed, AI-ready foundation grows with the 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 the in-house 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 one governed Snowflake core.
Governed and open by design
Built on Apache Iceberg and Open Catalog (Polaris) so data stays interoperable across engines and clouds.
Get it right the first time
Proven migration frameworks and certified architects reduce risk and rework when moving off Teradata, Oracle, Hadoop, or SQL Server.
Beyond dashboards to data agents
We ground Snowflake CoWork (the personal AI agent) and Cortex Agents in governed Semantic Views and Horizon Context, so business users get cited, trustworthy answers from the same definitions every team uses.
How engagements run
Checkpoints sponsors control
Clear timelines, steering, and a clean handover: the questions every sponsor asks, answered up front.
A fixed 8–16 week arc
Most initial builds reach production in 8–16 weeks: a paid discovery fixes scope and price up front, and every sprint closes with working software, so value lands from sprint one.
Steering & transparency
Regular steering reviews, a shared backlog, and clear decision gates keep sponsors in control of scope, budget, and priorities throughout.
Proof before scale
We prove the approach with a focused proof of concept before the full build, so the commitment to scale rests on evidence, not a slide deck.
Built to hand over
Runbooks, documentation, and enablement sessions ship with the build, plus a transition plan that names who runs what when we step back.
Business impact
What changes, and when
A practical view of the value an engagement returns, by horizon, not by feature list.
Foundations & first value
Scale & self-service
Compounding advantage
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 stand up a lasting data & AI practice.
Tell us where the organization stands (migrating, scaling, or shipping AI) and we'll map the fastest path to use cases in production, run by in-house teams.