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Enterprise AI Pilots

From business problem to working AI pilot — without a 6-month consulting cycle.

ALTE helps enterprise teams audit workflows, define AI opportunities, build controlled MVP pilots, configure the required infrastructure and prove measurable value before large-scale rollout.

Enterprise AI often moves too slowly.

Current state
×Too many strategy decks
×Too little product validation
×Internal teams are overloaded
×Procurement and security slow everything down
×Board wants proof-of-value
×Pilots fail without workflow ownership
Audit first

A controlled way to test AI before scaling it.

Before building, ALTE audits the real workflow, data sources and constraints — so the solution fits how the team actually works.

Request Workflow Audit
Use Case Selection
Workflow Audit
Risk & Security Review
Infrastructure Requirements
Pilot Scope
MVP Build
Proof-of-Value
Scale Roadmap
Infrastructure & Data

Secure infrastructure and governance for pilots.

We define the deployment environment, integrations, permissions, data access, governance and controlled pilot boundaries — so the pilot proves value inside enterprise security and procurement constraints.

Discuss Infrastructure Setup
  • Secure AI infrastructure
  • Enterprise AI governance
  • Data access control
  • Controlled pilot boundaries
Use cases

What we can build for you.

01

Internal Knowledge Assistant

02

Document Processing Workflow

03

Executive Reporting Assistant

04

Customer Support AI

05

Sales Operations AI

06

Compliance Assistant

07

AI Workflow for One Department

Case example

Enterprise AI Pilot — Internal Knowledge Search

Example pilot result — figures illustrative until a verified client case replaces it.

Problem. Employees spent too much time searching policies, files and internal knowledge.

Solution. Controlled AI knowledge assistant pilot for one department with permission-aware sources.

57%
faster retrieval
18%
fewer repeat questions
6wk
pilot validated
Process

How we build.

Discovery Call → Workflow Audit → Infrastructure & Data Review → Discovery Sprint → MVP Build + Infrastructure → Secure Launch & Scale.

1

Discovery Call

We identify the business problem, current workflow, expected outcome and potential AI opportunity.

2

Workflow Audit

We study your process, data, tools, users and constraints before defining what should be built.

3

Infrastructure & Data Review

We map data sources, access roles, integrations and deployment needs — and define personal data protection by design before any build.

4

Discovery Sprint

We turn audit findings into MVP scope, architecture, integrations, delivery logic and success metrics.

5

MVP Build + Infrastructure

We build the first working version, configure infrastructure and prepare secure deployment.

6

Secure Launch & Scale

We deploy, configure access, onboard the team, monitor feedback and prepare for wider rollout — data protected.

FAQ

Questions before we build.

Audit-first scoping, fixed scope, secure infrastructure and protected data — here is how ALTE works before a single line of production code ships.

Any questions? Reach out
How long does an enterprise AI pilot take?

We scope one department, one workflow and one measurable outcome — a controlled pilot typically validates within about six weeks.

We run a risk and security review, define data access control and governance, and keep the pilot inside controlled boundaries.

We deliver a scale roadmap covering infrastructure, integrations and rollout, so the decision to scale is backed by evidence.

Let's build

Ready to make your team faster?

Let's map your workflow and identify where AI can improve response time, quality and measurable outcomes.