Data connected.Agents enabled.Business processes supercharged.

VectorMachines connects your enterprise data, learns the language your business uses, and puts agents to work across it — automating cross-system questions, drafting actions, and routing only critical decisions to human approval.

runs inside your environment·agents act, humans approve·fully auditable
The problem

One cross-system
question shouldn't
take a week.

Today, a single answer that spans your databases, contracts, and email requires multiple analysts and the better part of a workweek. The bottleneck isn't the analysis — it's the reconciliation.

2–3analysts pulled in per cross-system question
4–5days to an answer — often after the decision has been made
The solution

How VectorMachines
works for your enterprise.

Connect your systems once. Resolve your team's language. Then ask our agents in plain-language — and act on the answer.

Finance · business process example

A GM's off-cycle ask — five engineers, none budgeted, to reach GA seven weeks sooner. Reconciling the payback across three systems by hand takes days.

01

Integrate

Connect databases, documents, email, and spreadsheets. Data stays where it is while we map sources, relationships, and gaps across systems.

02

Learn

Create a semantic layer across your data — entities, metrics, business terms, relationships, and source context — so agents understand how your business works.

03

Clarify

Platform surfaces ambiguous terms like revenue, close date, and active customer to your experts. Resolve them once and add the definitions back into the semantic layer.

04

Answer

Agents answer plain-language questions across connected systems. Every response is grounded in source data, cited, and traceable.

05

Execute

Agents draft the next action — a memo, report, update, or recommendation — and route designated actions for approval before execution.

Engagement model

Find your starting point.

Deployment scales with how customized your environment needs to be — from self-serve to fully embedded.

Standard Low customization
When to use. A couple of well-documented data sources and an internal analytics team.
  • Automated discovery
  • Self-service setup
  • Pre-built agents for finance, ops, and sales workflows
Live the same week.
Guided Medium customization
When to use. Several sources, a mix of databases and documents, a cross-team rollout.
  • Engineer-led setup
  • Custom data mappings and agent workflows
  • Team onboarding
Live in 2–3 weeks.
Embedded High customization
When to use. Complex, multi-system or regulated environments and enterprise-wide deployments.
  • Forward-Deployed Engineer on-site
  • Bespoke setup, custom agent design, and authority controls
  • Compliance and audit packaging
Live in 4–8 weeks.