An AI chat platform for Great Day Improvements — built on NeuralSeek.

Scale of the customer

Voice of the client

Soo-Jin Behrstock

Chief Technology Officer · Great Day Improvements

As CTO of Great Day Improvements, Soo-Jin leads technology strategy across the family of brands and partners with NeuralSeek on the yETI rollout covering HR and the Call Center.

LinkedIn →

Q: What parts of NeuralSeek impress you?

What stands out is how hands-on and engaged the team is. They're not just pushing a product — they're in it with us. When we bring up a use case, they work through it with us and quickly turn it into something real we can see and react to. That ability to move from idea to proof of concept fast has made a big difference for us internally.

Q: Thoughts on NeuralSeek having an implementation arm and experience doing enterprise go-lives.

There were some bumps along the way, which is expected in something this complex. What stood out was how Lawrence and Jordan (PM) brought in the right people at the right time to work through issues quickly. The team's experience and ability to apply best practices made a difference in keeping things on track. Once development was complete, they stayed engaged through iterative testing across different scenarios, partnering closely with us to make sure everything worked as expected before going live.

Q: General feedback on our team.

Overall, it's been a strong partnership. The team is responsive, easy to work with, and clearly cares about getting this right. They're available when needed, they bring ideas to the table, and they collaborate well with our team. It feels like a working session, not a vendor relationship.

About Great Day Improvements

• Home Improvement

  Industry & sector

• Azure Cloud

  Deployment — in Great Day's existing Azure tenant

• Est. 1966

  Flagship Patio Enclosures brand founded

• Macedonia, OH

  Headquarters, with a national footprint

• Private

  Privately held, PE-backed

• Multi-brand

  Patio Enclosures · Champion · Stanek · more

What's inside

1. 01

   Multi-LLM selection

   Users choose between multiple large language models inside yETI, matching the model to the task — concise answers, long-form reasoning, or domain-specific responses.

   Phase IModel choice
2. 02

   Authenticated access

   Every user signs in before entering yETI. User identity flows through each session so answers, history, and uploaded documents stay scoped to the authenticated person.

   Phase ISecure login
3. 03

   Document upload & analysis

   Users upload Word and PDF documents into the conversation and ask questions, summarize, or extract content inline — no separate analyst pipeline required.

   Phase IWord / PDF
4. 04

   Chat history & memory

   Every user sees their previous questions in a running history and yETI remembers prior turns within a conversation, so follow-ups stay contextual instead of starting from zero.

   Phase IContext-aware
5. 05

   Great Day knowledge preloaded

   Great Day Improvements' internal PDFs and Word documents are pre-indexed inside yETI, so users can ask natural-language questions about company policy, process, and product data directly.

   Phase IRAG
6. 06

   Azure-native deployment

   yETI is deployed end-to-end inside Great Day's existing Azure environment — no new cloud footprint, no data leaving the customer's tenant.

   Phase IIn-tenant
7. 07

   Phase II — Databricks integration & advanced document ingestion

   The next phase extends yETI into Great Day's Databricks datalake with OAUTH or SAML single sign-on, plus richer document ingestion for CSV, Excel, PDF, and Word — so analysts can upload structured datasets and have the chatbot reason over them alongside the existing corpus.

   Phase IIDatabricksSSO

KPIs at a glance