AI Solutions

AI that ships,
not slideware.

Most AI programs stall between the demo and the deployment. Ours don't. Every engagement pairs AI engineers with your domain experts and ends with something running in production, measured against a number you care about.

See it work

Ask your data a hard question.

This is the kind of system we build: an assistant grounded in your warehouse, your contracts, and your operational documents. It answers with numbers, names its sources, and knows when to say it doesn't know.

Scope an AI pilot

What we build

Five systems we ship again and again.

Knowledge assistants

Answers grounded in your documents, policies, and data, with citations on every claim. Retrieval tuned to your domain, evaluated continuously against a golden question set.

e.g. policy Q&A for a 4,000-person operations team

Workflow copilots

Drafting, triage, and review embedded in the tools your teams already use. The copilot handles the first pass; your people keep the judgment calls.

e.g. claims triage cut from 20 minutes to 90 seconds

Document intelligence

Extraction and classification across contracts, claims, invoices, and forms. Human-in-the-loop review queues for anything below the confidence bar.

e.g. contract clause extraction at 99.2% precision

Predictive operations

Demand forecasting, churn scoring, and anomaly detection running on live data, wired into the dashboards and alerts your operators already watch.

e.g. inventory forecast error down 42% year over year

Responsible AI, engineered in

Every system above ships with an evaluation suite, role-based access control, PII handling, and a full audit trail. Not a compliance afterthought, part of the architecture from the first sprint. When regulators or customers ask how the model decides, you'll have an answer.

Engineering depth behind these systems comes from our strategic collaboration with Orviniel Solutions, our AI build and delivery partner. Mindspace leads every engagement; Orviniel's product engineering bench helps us ship faster without compromising standards.

How a pilot runs

Working system in six weeks.

A pilot is not a slide deck. It's a scoped production candidate with real data, real users, and a go/no-go metric agreed on day one.

  1. Weeks 1–2

    Ground

    Pick the use case and the metric. Connect the data. Set the evaluation baseline the system has to beat.

  2. Weeks 3–5

    Build

    Ship the first working version in week three, then iterate against the evaluation suite with your users in the loop.

  3. Week 6

    Decide

    Measured results against the day-one metric, a production hardening plan, and an honest go/no-go recommendation.

Have a use case in mind?

Bring it to us rough. Scoping the right first pilot is exactly the work we're best at.

Scope an AI pilot