Will our data be used to train public AI models?

We design AI features with providers and settings that do not use your data for model training, and we document exactly where your data is processed and stored.

How do you make sure AI results are accurate?

We test AI features against real examples from your business, measure accuracy, and add human review steps for decisions that carry risk.

Do we need a lot of data to get started?

No. Many useful AI features, like document extraction or search across your knowledge base, work with the documents you already have. Forecasting is the main area where more history helps.

Data & AI Solutions

Data Engineering & AI Solutions

We turn scattered data into reliable reporting and add practical AI features, such as document processing, smart search and assistants, where they save real time.

Discuss your project Get a ballpark estimate

Is this the right fit?

We'd rather tell you up front when custom software isn't the best answer.

A good fit when…

Weekly or monthly reports are assembled by hand from several systems
People spend hours reading, sorting or re-keying documents
Answers are buried in manuals, policies, tickets or shared drives
You want to test an AI idea safely before committing to a large rollout

Probably not the best fit when…

Data with no clear owner or definitions yet. We'd start with a short data cleanup, not AI.
Fully automated decisions that must always be correct with no human review.

What we build

Dashboards & BI reporting

Clear, real-time reporting that replaces manual spreadsheet consolidation.

Data pipelines & warehousing

Collect, clean and centralize data from all your systems in one trusted place.

AI document processing

Extract data from invoices, forms and contracts with human review where it matters.

Smart search & assistants

Let your team ask questions across policies, manuals and records in plain English.

AI-powered workflows

Classify, route and summarize requests automatically inside your existing tools.

Forecasting & analytics

Demand, revenue and capacity forecasts built on your historical data.

Typical projects

Every project is scoped individually. These examples show the shape and size of work we commonly take on.

Management dashboard

Pipelines from three to five systems into one data store, with live dashboards for leadership.

Typical timeline: 6–10 weeks

AI document intake

Fields extracted from PDFs and emails, a human review queue and export to your ERP or accounting system.

Typical timeline: 6–10 weeks

Pricing

This work is scoped after a short assessment of your current setup. You'll receive a fixed-price proposal before anything starts.

Request an assessment

Our approach

01
Prove value with a pilot
A small pilot measured on real examples from your business before anything is scaled up.
02
Humans stay in the loop
Review steps and confidence thresholds wherever an AI mistake would be costly.
03
Privacy first
Clear rules on what data is processed, where it goes and how long it's kept.

What you get

Data audit and architecture recommendation
Automated, monitored data pipelines
Dashboards your team can explore
AI features with evaluation and human review
Privacy, access controls and data retention rules
Usage and cost monitoring

Technologies we use

Python
OpenAI
FastAPI
PostgreSQL
TypeScript
Next.js
Google Cloud
Docker

We choose the stack that fits your needs and your team's ability to maintain it, not the other way around.

How we work

Every project follows the same transparent process, with weekly demos and a written proposal before any work begins.

01Discover
02Design
03Build
04Launch
05Evolve

See how we work

Frequently asked questions

Have a project in mind?

Tell us what you're trying to solve. We'll get back to you within one business day with honest next steps, with no obligation and no sales pressure.

Start a project hello@lakebendsoftware.com