Expert analysis, on tap.
Insight Engineering is the Upside team you bring in when a question is too high-stakes, or your team too stretched, to run it in-house. They return it as finished work on your own data: board decks, custom models, and miniapps, deployed into your instance in days.
One engagement, start to finish
“New account directors are ramping. Get them up to speed on their books, fast.”— Head of GTM Ops
Already knows the data model. Has built this kind of work across dozens of datasets.
An Account Dossier: per-account engagement history, buying signals, competitive landscape.
Live on their data. Ramp time down, single-threaded deals flagged early.
One annual line item, not an open invoice
You've got this. We're your backup.
The platform is built so your team answers its own questions, builds its own apps, and runs its own analyses. Insight Engineering is who you call in when it counts: a high-stakes question you cannot get wrong, a stretch when you are short on time or hands, or an outside perspective on your GTM. And when you do call us in, it beats the alternatives.
The team already knows your data.
The value of a unified data layer depends on the questions you ask of it. Insight Engineering is the team that knows how to ask them well, on your data, because they have done the equivalent work many times before.
New hire or consultant
weeksInsight Engineering
daysWhat is a typical engagement, start to finish?
A sales org was bringing on new account directors and needed them productive on their books immediately. The standard dashboards weren’t built for instant territory handoff, so the question went to Insight Engineering.
An Account Dossier: a single per-account view, built on the customer’s own data and deployed inside their instance.
New account directors got an instant, complete view of their territory instead of stitching it together from CRM reports. The same analysis flagged single-threaded deals early, so managers could coach toward multi-threading before a deal slipped.
Account Dossier
Atlas Robotics · Enterprise · renewal Q3
Engagement history
Buying signals
Competitive landscape
Not just one kind of answer.
The work takes whatever shape the question needs, from a board deck to a model to an app, always built on your unified data and delivered where your team works.
Board-ready deck
Persona win-rate
Miniapp in your instance
Contact-role healing
runs live, not a one-off export
Scoring model
Upsell likelihood
Closed-lost analysis
Why deals slipped
Board-ready analysis. Persona win-rate tables, channel heatmaps, and competitive displacement findings, built from your enriched opportunity data.
Custom miniapps, deployed in your instance. Configured apps that run live on your data, like a contact-role healing app that corrects CRM gaps across the opportunity database, and that your team can keep evolving afterward just by describing the change to AI.
Predictive and scoring models. Account scoring for expansion and upsell likelihood, ranked against your own pipeline.
Inspector apps. Account-level views like intent signals with no open opportunity yet, surfaced for the team to act on.
Deep-research investigations. Closed-lost analyses and loss-pattern studies across hundreds of evaluated deals, returned as structured findings.
Built for the people who own the number.
Insight Engineering speaks to both tracks: the executive who needs a board-ready answer and the operator who needs a backstop.
Board decks, QBRs, and pipeline reviews need custom analysis a standard dashboard can’t produce. The team handles the translation from raw GTM data to a board-ready output, with methodology and presentation already validated, and off your analyst’s deadline queue.
A backstop for analyses too important to get wrong and too complex to build quickly in self-serve: data quality investigations and custom apps that run inside your instance. The team can also teach you to replicate the work.
Procured as an annual line item, not variable consulting hours. Fixed cost, scope agreed in advance, outputs defined. An extension of platform value, not a separate professional-services relationship with open-ended billing.
Always there, plus on demand.
Insight Engineering is an ongoing relationship, not a one-off invoice. Every engagement comes with a standing line to the Upside team, and bigger projects on tap when you need them.
Ongoing Slack support
A shared channel with the Upside team
Regular check-ins
Standing syncs to keep analyses pointed at what matters
On-demand projects
Board decks, models, miniapps, deep-research — on tap
When teams bring us in.
Cresta brought Insight Engineering the analysis behind every quarterly business review. Weeks of manual transcript review collapsed into a single day, and the work became the engine of the QBR itself.
“Like working with a therapist, a data consultant, a friend.”
An Insight Engineering analysis of inbound versus outbound contribution gave Syndio the evidence to strategically restructure their ADR function, the kind of call an engagement can drive that a standard dashboard never surfaces. Read the Syndio story →
We work on the platform you already run.
Insight Engineering is not a separate consultancy. It is the Upside team working on the same reconstructed data foundation the rest of the platform runs on, with the same tools.
Every engagement starts from your unified, healed GTM record.
The same analytical engine and surfaces the platform ships, applied as a service.
Have a specific job in mind, like multi-touch attribution or a closed-lost deep dive? Start from the use case: Use Cases →
Frequently asked questions
Is this just consulting?
No. The work is done by the team that built your data platform, on the same healed data, with the same tools, and it is priced as a fixed annual line item with defined scope, not open-ended hours. The outputs run in your instance, not in a vendor’s deck.
What can the Insight Engineering team build?
Board decks, predictive and scoring models, miniapps that run live in your instance, and deep-research investigations like closed-lost analyses. If it can be built from your unified GTM data, it is in scope.
Do we own the outputs, and can we replicate them ourselves?
Yes. Deliverables run in your instance and on your data. Some teams use a first engagement specifically to learn how to do the work in-house.
How fast is it?
Most engagements come back in days rather than the weeks or months an equivalent internal project would take, because the team already knows your data model and has built comparable analyses before.
Does it replace our analyst team?
No. It is a backstop for the analyses too important to get wrong or too complex to build quickly in self-serve, so your team’s time goes to the work only they can do.
How is it different from Deep Research?
Deep Research is the self-serve product you run yourself. Insight Engineering is the team running it, and more, for you: scoping the question, designing the analysis, and deploying the result into your instance.
Bring us the question you keep postponing.
Pick one real analysis your team hasn’t had time to run, and we’ll scope it with you.