The company has 2-4 workflows ready for implementation.
AI Transformation
AI IMPLEMENTATION
90-Day AI Implementation Sprint
A 90-Day AI Implementation Sprint builds 2-4 production AI-enabled workflows, trains the team, installs human review and evaluation, and measures whether the workflows improve speed, quality, response, or operating visibility.
USE THIS WHEN
When this service is the right fit.
Use this service when these conditions are present. If the first workflow is still unclear, start with the AI Opportunity Score.
Process owners can meet weekly and test outputs.
Leadership wants measurable operating improvement, not a pilot nobody owns.
The team accepts human review, training, and monitoring as part of the build.
WHAT YOU GET
What your team can use immediately.
Each engagement leaves owners, review rules, and a practical way to measure whether the workflow improved.
Deliverables
- Sprint backlog and implementation scorecard.
- Workflow redesign.
- 1-4 AI-enabled workflows or agents.
- Integration with existing tools where feasible.
- Human-in-the-loop review and evaluation process.
- Employee training and SOPs.
- KPI baseline and weekly operating review.
- Scale and maintenance plan.
What we will not automate without review
- No unsupervised customer-facing, financial, legal, employment, or regulated decisions.
- No workflow goes live without owner sign-off and rollback path.
- No scale-up until quality, usage, cost, and exception handling are visible.
SAMPLE WORKFLOWS
AI belongs in a workflow, not a demo.
These examples show the before and after state. The actual design is scoped around the client's systems, data, risk, and team.
Support triage
- Before
- Tickets wait for manual classification and knowledge search.
- After
- AI suggests category, urgency, summary, draft response, and escalation route.
Sales follow-up
- Before
- Account research and next steps vary by rep.
- After
- AI prepares account context, next-best-actions, and reviewable follow-up drafts.
Back-office routing
- Before
- Invoices, contracts, and requests move through inbox memory.
- After
- Documents are classified, summarized, and routed to the right owner.
HOW WE WORK
Workflow first. Tool second. Review always.
The cadence is deliberately practical: scope, build or blueprint, train, measure, and decide what should scale.
- 01
Confirm sprint backlog, success metrics, owners, data access, and risk boundaries.
- 02
Redesign the workflow before building automation.
- 03
Build in weekly increments with process-owner testing.
- 04
Train users, document SOPs, and hand over monitoring cadence.
RELATED AI PATHS
Choose the next relevant path.
Use these role, function, industry, and service pages to move from a general AI question to the specific workflow in front of you.
RELATED INTELLIGENCE
Operating analysis for practical AI decisions.
These articles cover governance, vendor risk, team readiness, technical debt, and automation design in more depth.
Where AI agents work for small businesses, where they fail, and how to set permissions, logs, approvals, and human review before deployment.
AI consulting cost ranges for small businesses, including audits, roadmaps, implementation sprints, governance work, and ongoing AI operating support.
A practical guide to choosing the first AI workflow for a small business, with scoring criteria, risk boundaries, and examples across sales, support, operations, and finance.
How to use AI for CRM cleanup before sales automation, including duplicate detection, account enrichment, stale stages, next-step hygiene, and forecast trust.
Customer service AI use cases to automate before buying a chatbot: ticket triage, knowledge retrieval, draft responses, QA, escalations, and trend analysis.
The difference between an AI pilot and a production workflow: ownership, data controls, evaluation, training, exception handling, and ongoing measurement.
FAQ
Questions leaders usually ask.
How many workflows fit in one sprint?
Most SMB sprints cover two production workflows. Mid-market sprints may cover three or four if data access and owner availability are strong.
Do you build agents in the sprint?
Yes when agents are the right design, but the sprint starts with workflow readiness and human review before agent behavior is expanded.
What does production mean?
Production means real users, real work, documented SOPs, monitored outputs, and named owners. It does not mean unsupervised autonomy.
Can we use our existing tools?
Usually. We prefer to build around the systems the business already uses when they are fit for purpose.
How do you measure success?
We baseline and review cycle time, response quality, rework, throughput, adoption, cost, and the business metric the workflow is meant to improve.
What happens after the sprint?
Teams usually move into Managed AI Workflow Support or Fractional AI Transformation Partner support to keep workflows healthy and expand the backlog.