AI Deployment Squad
Ship one working AI agent in four weeks.
Our embedded technical squad joins your business unit, builds the agent, integrates it with your stack, measures it with real users, and hands it off with ownership in place.
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What the Squad Delivers
Three things that make the sprint valuable, not just fast
A Working Agent
A real assistant or workflow agent connected to your data, identity layer, and the process your team actually wants to improve.
Measurement from Day One
An eval set, KPI baseline, and user feedback loop so quality and adoption are tracked as part of the build, not after launch.
Handoff You Can Operate
Runbooks, architecture choices, governance notes, and knowledge transfer so your team can own the system after we step out.
Outcomes
What changes by the end of the sprint
Live pilot with users
Your agent is tested by real people on real work, not just shown in a demo environment.
Integration path cleared
Auth, data sources, security review, and operating assumptions are worked through with your team.
Operating playbook
Your team receives the runbook, monitoring logic, and extension path for what comes next.
Ownership transition
The sprint ends with leadership review, KPI visibility, and a clear recommendation on whether to scale.
Who This Is For
Teams with one high-value AI use case that should already be live: customer-facing assistants, internal RAG copilots, workflow agents for operations or sales, and business units that need external execution power to ship on the right timeline.
Inside the Four Weeks
Every week has a purpose. The structure is designed for speed without skipping architecture, evals, or ownership.
Frame
Scope the use case, define eval criteria, align on architecture, and clear data and security assumptions.
Build
Create the core agent, retrieval pipeline, and integrations required to run against your actual stack.
Pilot
Run with real users and real data, measure the outputs, and iterate based on what the evals show.
Hand Off
Deliver runbooks, KPI view, knowledge transfer, and a leadership review with what worked and what comes next.
Engagement Snapshot
What the squad model looks like in practice
Format
- 4 weeks, extendable
- Embedded delivery squad
- Remote or on-site
- Weekly working review with your stakeholders
Who Joins
- 2-4 ApplAI engineers
- Your business owner
- IT or data counterpart
- Security stakeholders when needed
What We Need
- One high-value use case
- Access to the right systems and people
- Fast feedback loop with users
- Clarity on success metrics
About ApplAI
ApplAI is a consulting and AI implementation firm for enterprise organizations. We combine strategic judgment with delivery experience inside environments that care about security, ownership, and measurable results.
That operator mindset is what lets us build fast without leaving your team with a fragile prototype.
Frequently Asked Questions
The best fit is a focused workflow with clear users, clear data sources, and a measurable operational outcome, such as support, research, knowledge work, internal service delivery, or management reporting.
We usually need one business owner, access to the relevant subject-matter experts, and enough IT participation to unblock systems, permissions, and security review as the build progresses.
Yes, when access and approvals allow it. We design the architecture around your stack, whether that means APIs, document repositories, internal knowledge bases, or a more controlled staging approach.
We define success in operational terms up front, such as time saved, response quality, throughput, adoption, or reduction in manual work, and then test against real usage during the sprint.
From there we either hand off with documentation and support, extend into another sprint, or use the first deployment as the template for a broader internal rollout.
Interested? Let's Talk
Tell us what you want to ship and we'll tell you if a four-week squad is the right fit.