Ask your business a plain question, get a real answer.
Most businesses already have the data they need. It is just in three different places, formatted three different ways, and none of them talk to each other. We build the layer that lets anyone on your team ask a question in plain English and get a real answer back, with the source row attached.
What is a conversational data layer?
A conversational data layer is a single interface built over your existing data, including CRM, spreadsheets, databases, and documents, that lets anyone on your team ask a question in plain English and get a real answer back, with the source row attached. No dashboard to maintain. No analyst to book. No hour spent reformatting a spreadsheet before you can see what is happening.
Most businesses have the data they need. It is just in three different places, formatted three different ways, and none of them talk to each other. Getting a straight answer out of it means running a report, booking time with someone who knows the system, or spending an hour reformatting things into a shape that answers the question you actually had. The problem is not the data. It is the gap between the question and the answer, and that gap costs time on every decision your team makes.
What is included in every build
- 01Data mapping, we document every source your business currently uses to store and retrieve information, including the unofficial ones that actually run the company
- 02Integration and connection, we connect the sources into a single queryable layer. Where data is inconsistent or duplicated, we resolve it as part of the build
- 03Natural language interface, your team asks questions in plain English. The layer returns answers with the source row or document attached
- 04Full handover, repository, credentials, runbook, and every prompt in source control. Yours from day one
Common shapes
- aReporting on demand without a BI seat per person
- bCustomer or order lookup across multiple systems at once
- cOperational data Q&A over five plus years of historical records
- dCompliance and audit queries with citations sufficient for evidence
Where to go next
A conversational data layer pairs naturally with workflow agents that act on what the data tells you, and with bespoke internal tooling built around your stack. The fastest way to find the right starting point is to run the audit.
Ask the business, professional services firm
Names are kept private. Outcome and numbers are real.
Data layer, specifically.
General questions live on the services hub. These are the ones we hear most about a data layer in particular.
The retainer. Where the build keeps earning.
Builds rarely fail on the day they go live. They fail around month four, when the systems around them move and nobody inside has the time to keep up. Monthly, rolling, thirty days notice.
It keeps working.
We watch it. When something it leans on changes, a field in the CRM, an API version, the shape of a form, we fix it before it turns into your problem on a Monday morning.
It keeps matching the work.
Your process moves and the exceptions change. We tune the prompts, the rules and the escalation thresholds so the output stays right instead of drifting away from how you actually work.
It keeps growing.
Every month carries build time for the next thing. The system widens into the work next door rather than standing still at whatever it did in week one.
You own it either way. The repository, the prompts, the keys and the runbook are handed over on day one of go live and stay yours whether we carry on or not. That is deliberate. A retainer you can end in thirty days has to earn its place every month, and that is the only sort worth selling.
Talk about the retainer →Scope a data layer.
Bring the process. We map it, find the bottleneck, and write a one page recommendation with a fixed price, yours either way.
Book a conversation →