Pricing & engagement

Clear scope. No surprises.

Viewnear prices engagements three ways: fixed cost for a defined outcome, time and materials while scope is still evolving, or an embedded team. Scope and price are agreed up front.

How we work

Engagement models

Flexible ways to partner, matched to the shape of the problem: fixed-outcome delivery, flex capacity, or a dedicated team embedded in yours.

Fixed cost№ 01

A defined scope, timeline, and price agreed up front: fixed-outcome delivery, priced to the result rather than the hours. Best when the outcome is clear and budget certainty matters from day one.

Best forDefined foundation builds & migrations

Time & materials№ 02

Flexible, iterative delivery billed by effort against a shared backlog. Ideal for evolving requirements and discovery-led work.

Best forDiscovery, POCs & evolving scope

Dedicated team & staff augmentation№ 03

Embed our certified practitioners alongside the in-house team, as a dedicated team or a team extension. We accelerate delivery while leveling up their capability.

Best forScaling an existing team fast

Whichever model fits, the team is nearshore and on your hours.

How delivery works→

A worked example

The shape a first engagement is scoped to: a discovery fixes scope and price, sprint demos show working software from the first weeks, and a governed foundation reaches production in 8–16 weeks, with a named team the sponsor meets before signing and in-house people in the work from sprint one.

What drives cost

Priced to the work, not a sticker

We don't publish one-size pricing because no two engagements 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

Get a scoped estimate→

Practice adoption, by horizon

First 8–16 weeks
Foundations & first value
The data practice stands up: scope fixed in discovery, governance designed in from the first table, priority data flowing, and the first governed data products in production.
6–12 months
Scale & self-service
The AI practice ships: use cases spread across teams, and each new one starts from the governed foundation the last one built. Self-service takes hold; manual reporting retires.
18+ months
Compounding advantage
Both practices are in-house: new use cases ship in weeks, and run cost keeps falling as sizing and scheduling are tuned, and the handover is real. The team runs and extends the work without us.

Proof

What an engagement looks like

View all case studies→

Insurance · Americas

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.

Education · Miami & LATAM

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 Anthology Illuminate Developer integration, and real-time Caliper event streaming, unifying academic and learning-activity data into one governed source.

Automotive · Mexico

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 is building a corporate master data foundation on Snowflake, released domain by domain: a progressive multi-source golden record across eight business domains, using a Medallion architecture, Openflow ingestion, dbt transformations, and per-domain Snowflake CoWork agents.

Talk to a person

Book 30 minutes with the person who can actually answer

Not a qualification call with an SDR working from a script. You get one of the people who would actually own the build. They will tell you what is achievable and in what order, and if Snowflake is the wrong answer for what you need, you will hear that too.

You leave with a sequence you can act on, whether or not you work with us.

What the 30 minutes covers