Bomshteyn
Consulting

Canadian-led · Serving businesses across the US and Canada

AI business automation, built around your work

Give your staff a better way to work through invoices, documents and business questions without handing control to a black box. We build AI automation for established businesses, connecting useful AI steps to the systems you already depend on.

Talk through your workflow

  1. 01

    Your systems

    Business records and definitions remain under your control.

  2. 02

    An AI-assisted step

    Query approved data or turn a document into a draft.

  3. 03

    A person decides

    Check the source, resolve exceptions and approve the next step.

Less retyping. Clearer answers. People still in control.

AI automation services connect useful tools to a specific piece of work. We start with the repeated task, the source information and the decision someone needs to make. These patterns come from systems we have built.

01

Ask questions of your own business data

We have built read-only MCP connectors that let ChatGPT and Claude query business databases for rental-management and charity reporting. Editable business definitions explain which records, dates and amounts belong in an answer.

The connector brings those definitions into the reporting conversation, so the owner can investigate a question using the business's own records. Clear source boundaries help distinguish overlapping donations, different reporting periods and incomplete data.

02

Turn vendor invoices into draft orders

In a buying-group portal, we built invoice and PDF ingestion using Gemini to extract information and prepare draft orders. The extracted details feed the existing order workflow, giving staff a concrete starting point.

A reviewer checks the draft against the source document and resolves unclear items before accepting the order. This keeps approval with the people responsible for purchasing while reducing preparation work.

03

Connect documents, email and operational work

We have built email-integrated order management that brings messages and replies into an order portal. Staff can follow work and responsibility from the order record.

Our healthcare work also includes EOB, or explanation of benefits, and document parsing for billing workflows. Each connects incoming information to the business record and its review process.

04

Compare reports without losing the business meaning

Our connector work includes cross-referencing business records with uploaded accounting exports. Editable business definitions make the date basis, source scope and treatment of overlapping records explicit.

That context helps the person reviewing a report follow the evidence. It also gives staff a way to investigate differences between operational records and accounting entries.

Start with paid discovery. Build in useful phases.

Our AI automation consulting begins with understanding the operation, not selecting a model. Delivery is Canadian-led, with our senior developers in Europe building Laravel/PHP systems around the agreed workflow. You work toward a defined next step.

  1. 01

    Map the work and the boundaries

    Paid discovery looks at the task as staff do it today: where information arrives, what gets copied, who checks it and what happens when something is wrong. We identify the source systems, access permissions and business definitions. Together we choose a bounded first use case and decide what must stay manual. The discovery output gives us a basis for scope and phased delivery.

  2. 02

    Build one reviewable workflow

    We implement an initial phase against the agreed task and review it with the people who will use it. For a reporting connector, that means approved read access and clear definitions. For document ingestion, it means a draft and an explicit review point.

    We work through representative records, missing information and awkward examples. Your team can judge whether the result fits the real job before extending it.

  3. 03

    Extend what earns its place

    Later phases can connect another source, handle another document type or improve the review experience. We agree each phase around a concrete operational need. Your database and operational records stay in your systems; AI is a controlled connection, not a replacement source of truth.

    Where an external AI provider processes selected query results or document content, we agree that boundary with you. Human approval remains part of consequential decisions.

The operational systems behind the work

Explore the operational foundations of this work: email-connected orders, invoice ingestion, healthcare financial reporting and charity record management.

Questions about AI automation for business

What should we automate first?

Start with a repeated task where the input, desired output and reviewer are clear. An invoice that becomes a draft order or a recurring reporting question is easier to evaluate than a broad request to automate a department. Discovery also checks whether an ordinary integration would solve the problem without AI.

Will AI be able to change our records?

Reporting connectors are read-only by default. Document ingestion is a different workflow: it can prepare drafts for people to review, rather than silently changing approved orders. We define access and approval boundaries for the specific system. The ability to read information is not permission to make purchases, issue receipts or release payments.

Does our data stay in our systems?

Your operational database remains in your systems and stays the source of truth. Using an external AI service can send selected query results or document content to that provider for processing. We agree what may be shared, which provider is involved and what access is needed before building.

Do we need to replace our existing software?

Not necessarily. A read-only connector can sit alongside a business application, and document preparation can feed a defined review workflow. We first check the available database, APIs and exports. If the source data is incomplete or the system cannot safely support a connection, that becomes a discovery finding rather than a hidden assumption.

How is this different from hiring an AI automation agency for a chatbot?

Our focus is the work behind the business: reporting, invoices, documents and connected operational systems. A conversational interface can be useful, but it needs business definitions, controlled access and a way to check the answer. We build around those requirements rather than treating a chatbot demonstration as a finished business process.

Related services

Bring us one workflow that keeps getting in the way.

Tell us what arrives, where it gets entered and who has to check it. We will talk through whether a read-only connector, a document-to-draft workflow or a straightforward integration is the right place to begin. The next step is a conversation about your operation.

Start a project brief
DWG SVC · 01
Label AI automation
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