Pricing & engagement
Clear scope. No surprises.
Engagements are scoped to your data and goals, and priced up front, whichever model fits. Here's how we structure the work and what shapes the investment.
How we work
Engagement models
Flexible ways to partner, matched to the shape of your problem.
Fixed cost
A defined scope, timeline, and price agreed up front. Best when the outcome is clear and you want budget certainty from day one.
Best for: defined platform builds and migrations
Time & materials
Flexible, iterative delivery billed by effort against a shared backlog. Ideal for evolving requirements and discovery-led work.
Best for: discovery, POCs, and evolving scope
Team augmentation
Embed our certified practitioners alongside yours. We accelerate delivery while leveling up your in-house capability.
Best for: scaling an existing team fast
What drives cost
Priced to the work, not a sticker
We don't publish one-size pricing because no two platforms are the same. Cost is shaped by:
- Data volume and the number/complexity of source systems
- How many analytics and AI use cases are in scope
- Team size and target timeline
- Governance, compliance, and security requirements
Value by horizon
- First 90 days
Foundations & first value
Governance in place, priority data flowing, first production dashboards.
- 6–12 months
Scale & self-service
Use cases across teams; self-service adopted; manual reporting retired.
- 18+ months
Compounding advantage
New use cases in weeks, run cost tuned, with a team fluent enough to extend it themselves.
Proof
What an engagement looks like
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 scope it together.
Tell us your goals and constraints, and we'll come back with a model, a plan, and a price you can take to the board.