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DataGrine

Use cases

The situations teams actually bring us.

Not industries - situations. Each one has a specific hard part, and it is usually not the part people expect when they start looking for a migration tool.

These are patterns, not case studies. They describe the shapes of work we take on. Named client stories will replace them as those are written up and approved.

Platform switch

You signed with a new platform and go live in six weeks.

The contract is signed, the date is set, and four years of ticket history is still sitting in the old desk. Everyone is focused on the new tool; nobody owns the history.

The hard part

The records and the configuration are two different projects with one deadline. Teams routinely solve the first and discover the second the week they go live.

What the work is

  • Mapping document covering every object and field, signed off before anything moves
  • Dry run into a sandbox on the destination for you to check
  • Bulk migration over a weekend, delta sync on cut-over day
  • Triggers, macros, SLAs, views and routing rebuilt in the new platform

Done looks like: Agents log in on Monday, search a customer, and find the whole history - with the macros and views they already know.

Consolidation

Two support desks after an acquisition, one team from Monday.

Two companies, two help desks, two sets of tags, two definitions of “urgent”, and overlapping customer records across both.

The hard part

Merging is not moving. Contacts and companies exist on both sides, the taxonomies disagree, and a naive import doubles every customer.

What the work is

  • Deduplication rules on email, domain and external ID, agreed with you up front
  • Tag and field taxonomy reconciled into one scheme before the move
  • Both histories merged into one destination with source visible on every record
  • One set of workflows, SLAs and views for the combined team

Done looks like: One desk, one taxonomy, no duplicate customers, and history from both companies searchable in the same place.

Data residency

Your data has to live in a specific region - or in your own cloud.

A contract, a regulator or a security review requires customer data to stay in a nominated region, or never to sit on a vendor’s infrastructure at all.

The hard part

Most migration tooling is SaaS: your data passes through somebody else’s account by design. That is precisely the thing under review.

What the work is

  • Engine deployed inside your own AWS or Azure account, in the region you nominate
  • Least-privilege API credentials, with the scopes documented and justified
  • Regional hosting move on the destination platform coordinated with the vendor
  • Written confirmation of access revocation at hand-over

Done looks like: The migration completes without customer data leaving your infrastructure, and security review has the document trail it asked for.

AI readiness

You bought an AI agent and the answers are not good enough.

Fin (or an equivalent) is live, deflection is below what the business case assumed, and everyone is arguing about the model.

The hard part

It is almost never the model. It is stale articles, contradictory answers, content the agent cannot reach, and no explicit rules about where it should stop.

What the work is

  • Content audit: what exists, what is stale, what contradicts itself
  • Articles restructured so an answer is one hop away, not four
  • Actions and data the agent may use, defined deliberately
  • Hand-off rules and a measurement plan so “is it working?” has an answer

Done looks like: The agent answers the questions it should, hands over cleanly on the ones it should not, and you can see which is which.

B2B support

Your customers live in shared Slack channels now.

Enterprise customers refuse to open tickets. Support is happening in Slack, and the help desk is becoming a system of record nobody updates.

The hard part

Moving to a Slack-native desk means collapsing conversation threads into a different issue model without losing authorship, timestamps or the internal-note boundary.

What the work is

  • History migrated into the new platform with accounts resolved correctly
  • Account and contact mapping so history attaches to the right customer
  • Triggers, macros and assignment rebuilt in the destination
  • Knowledge base moved with redirects from the old URLs

Done looks like: Support happens where customers already are, and the years of history that came before it are still searchable.

Knowledge base

You are moving the help centre and cannot lose the search traffic.

The knowledge base ranks. It answers questions before they become tickets. Moving it badly costs deflection and organic traffic at the same time.

The hard part

Article structure, authorship, published state and URLs all change shape between platforms - and search engines notice.

What the work is

  • Content, collections, authorship and published state migrated intact
  • URL map produced and redirects implemented from the old paths
  • Images and inline assets re-hosted and re-linked
  • Post-move crawl to catch anything that 404s

Done looks like: The help centre lands on the new platform with its structure intact and its existing traffic still arriving.

Who we work with

Three people usually sit on the call.

They want different things from the same project, and a migration plan has to answer all three.

Support and CX leads

You own the go-live date and the team that has to work on Monday. You want certainty about what carries across, in writing.

Support ops and admins

You are the one rebuilding 60 macros and 40 triggers by hand. That is the work we take off your desk.

IT and security

You need to know where the data goes, which scopes are used, and how access ends. Self-hosting is available when the answer has to be “nowhere but here”.

None of these quite match?

Most migrations have one detail that makes them awkward. Tell us yours - you will get a straight answer about whether it is hard, routine, or not worth doing at all.

  • A written mapping document before anything moves
  • A dry run you review in a sandbox
  • Fixed price, agreed up front
  • The workflows rebuilt too, where we implement