Accelerate the Path From Problem to Value.

Most enterprises have more AI opportunities than they can realistically pursue. The challenge is separating promising ideas from the workflows where AI can create meaningful, measurable value.

Foxtrot works alongside the people closest to the work to understand critical workflows, identify where AI can have the greatest impact, and prioritize the opportunities worth pursuing. The Sprint turns those opportunities into a focused roadmap for production, including a clearly defined first build.

AI agents are moving into production faster than many organizations can answer three basic questions: who approved them, who monitors them, and who owns the outcome? As agents operate across systems, models, data, and workflows, maintaining clear ownership, permissions, human oversight, and accountability becomes increasingly important.

This accelerator creates one governed operating view of every agent, its owner, permissions, risk level, human-review points, and audit history. Teams gain greater visibility into what agents can do and access, where human review is required, and who is accountable, helping organizations scale agentic AI with stronger control and traceability.

Enterprise data platforms rarely stay clean on their own. As teams build applications, launch new use cases, and scale AI, unused datasets, orphaned assets, duplicate objects, inconsistent naming, outdated permissions, and unnecessary compute accumulate.

Over time, that complexity increases cost and maintenance, makes the ontology harder to trust, and makes it harder to understand what exists, who owns it, and whether it is secure.

This accelerator assesses ontology and platform health, surfaces the highest-priority risks and inefficiencies, and provides a practical roadmap to reduce unnecessary cost, strengthen governance, improve platform trust, accelerate development, and ensure the operating layer can scale with the business.

AI can look affordable in a pilot. At scale, token usage, compute costs, and model usage can add up fast. As spend spreads across models, cloud environments, teams, and workflows, it becomes harder to see what is driving cost, who owns it, and what business value it's creating.

Foxtrot's AI Spend & Control Diagnostic provides greater visibility into AI usage, spend, ownership, and value. It surfaces duplication, underused tools, and avoidable compute, while identifying opportunities across token optimization, intelligent model routing, context management, caching, workload optimization, and cost attribution to improve AI economics without sacrificing performance.

Manual redaction is slow, difficult to scale, and costly to get wrong. As document volumes grow, teams struggle to maintain speed, consistency, and a defensible record of every decision.

RedacSure identifies sensitive information, explains why each redaction was recommended, and routes final decisions through human review. Teams can process FOIA, PHI, legal, and other sensitive documents faster while preserving control, traceability, and audit-ready outputs.

Regulatory change rarely affects just one part of the business. From changing financial regulations to emerging AI governance requirements, organizations must determine what changed, understand the business impact, and coordinate action across policies, controls, teams, and increasingly complex operations.

This accelerator helps organizations turn regulatory change into accountable action, translating new requirements into a clear action plan, with impacted areas identified, assigned owners, tracked actions and deadlines, and evidence of completion. Teams can respond faster, avoid last-minute scrambles, expand into new markets, launch regulated products with greater confidence, and address gaps before they become findings or expensive remediation.

Projects and operations generate thousands of signals across tickets, status updates, customer feedback, blockers, cases, and changing priorities. The challenge is knowing which signals matter most, where risk is emerging, and what needs attention early enough to prevent smaller issues from becoming larger operational problems.

This accelerator brings those signals into a clearer operating view, prioritizes cases and alerts, and helps route high-priority work to the right people. Teams can intervene sooner, focus their time and judgment where it matters most, and maintain greater consistency as volumes and complexity grow.

Critical business information is everywhere, and rarely where teams need it. It is scattered across PDFs, spreadsheets, scanned forms, contracts, reports, calls, and recordings. Finding it, reconciling it, and entering it into other systems slows analysis and leaves valuable information underused.

This accelerator uses AI to identify, extract, validate, and structure the information that matters so it can flow directly into analysis and downstream workflows. Teams spend less time searching, transcribing, and rekeying information, and more time acting on faster, more complete insights.

Whether onboarding a new client or a new engineer, delays often stem from the same challenges: fragmented documentation, disconnected systems, manual handoffs, competing priorities, and limited visibility into progress. The result is longer time to value, unnecessary operational overhead, and inconsistent experiences for both employees and customers.

This accelerator helps organizations streamline onboarding by bringing people, processes, systems, approvals, and information into a connected, repeatable workflow that surfaces issues earlier, improves visibility and consistency, and accelerates readiness, helping teams move from onboarding to productive work faster.