AI Strategy & Roadmapping
Discover where AI creates genuine value in your organization, assess your readiness, and build a multi-year plan your team can actually execute — grounded in your real constraints, not vendor hype.
Learn moreTapestries Group helps organizations discover where AI creates real value, build the roadmap to get there, and execute with senior practitioners who stay through delivery — not a firm that wins the work and hands it off.
From discovering where AI actually creates value in your organization to building systems worth shipping — and making sure they're ready for production.
Discover where AI creates genuine value in your organization, assess your readiness, and build a multi-year plan your team can actually execute — grounded in your real constraints, not vendor hype.
Learn moreStructure your AI initiative backlog with clear priorities, defined success criteria, and honest dependency mapping — so your engineering team ships the right things in the right order, not just the most exciting ones.
Learn moreCustom LLM integrations, agentic workflows, and retrieval-augmented systems built by practitioners who understand the tradeoffs — not a team that learned the technology last quarter.
Learn moreRetrieval-augmented generation architectures that give AI systems access to your organization's knowledge — designed with proper access controls, data boundaries, and pipelines that stay current.
Learn moreSecurity assessments, threat modeling, and compliance readiness (HIPAA, SOC 2, FedRAMP) for AI systems heading to production — integrated into your development process, not bolted on at the end.
Learn moreExecutive-level guidance on AI governance, vendor and build-vs-buy decisions, organizational readiness, and the change management that determines whether an AI program actually takes root.
Learn moreA disciplined three-phase approach that gets to value quickly and builds capability that outlasts our engagement.
We assess where you are — your data, your infrastructure, your team's capability, and your organization's actual appetite for AI — and identify where AI creates genuine, defensible value. No hype, no vendor-sponsored use cases. An honest picture of opportunity and constraint.
A prioritized roadmap and structured AI backlog: what to build first, why, how to measure success, and what you need in place before you start. Dependencies mapped, risks surfaced, and a plan your engineering team can actually execute without heroics.
Iterative development by the same senior practitioners who created the plan — with continuous validation against real business outcomes, not just technical delivery milestones. Knowledge transfer built in so your team owns the solution when we're done.
AI strategy only works when it's grounded in the specific constraints, regulations, and competitive dynamics of your industry. Generic playbooks don't survive contact with your business.
AI for fraud detection, credit risk, client servicing, and operational automation — navigated with the data governance, model explainability, and regulatory requirements the industry demands.
AI strategy in HIPAA-governed environments: clinical documentation, prior auth, patient engagement, and operational efficiency — with compliance built in from the first architecture decision.
AI that augments high-value knowledge work — research, drafting, analysis, and client delivery — without introducing liability, hallucination risk, or the data exposure your clients would not accept.
AI strategy and backlog planning for teams that need to move fast without building technical debt that makes the next round harder. Senior guidance without enterprise overhead or enterprise timelines.
AI for predictive maintenance, quality control, supply chain optimization, and production planning — connected to the real constraints of OT environments and operational data that's never clean.
Personalization, demand forecasting, customer service automation, and merchandising intelligence — built on data you already have and tuned for the margin pressure retail operates under.
Most consulting firms operate on a leverage model: senior partners sell the engagement, then hand it off to analysts who are learning AI on your budget. You get billed at senior rates for junior execution, and a strategy document nobody can implement.
At Tapestries Group, the consultant who scopes your engagement is the one who delivers it. Every engagement is led by a senior practitioner with real-world experience building and deploying AI systems — someone who has made the mistakes, learned from them, and knows how to keep you from repeating them.
A concrete, prioritized AI roadmap and backlog — not a slide deck of AI use cases your team can't execute. Depending on scope, you'll get an opportunity assessment that identifies where AI creates defensible value in your specific context, a multi-year plan with sequenced initiatives, a structured backlog with epics and acceptance criteria, and a clear view of what you need in place (data, infrastructure, org capability) before each initiative can succeed. It's designed to hand directly to an engineering team, not to sit in a SharePoint folder.
Engineering teams are great at building things. AI strategy consulting answers the questions upstream of building: which things are worth building, in what order, and whether the organizational and data foundations are in place to make them succeed. Many of our clients have strong engineering teams that have been spinning on AI initiatives for a year without meaningful outcomes — not because of technical failure, but because the strategy and backlog weren't structured around real business value. We fix that first, then help you build.
AI backlogs have different failure modes than traditional software backlogs. Stories are harder to estimate, dependencies on data quality and model performance are non-obvious, and "done" is harder to define. We structure AI backlogs with explicit success criteria tied to business outcomes, data and infrastructure prerequisites surfaced as dependencies, staged experiments with clear go/no-go criteria, and scope boundaries that prevent initiatives from ballooning as the model evolves. The result is a backlog your engineering team can commit to, not one that collapses under contact with reality.
A focused AI opportunity assessment and roadmap — the most common starting point — typically runs $15,000–$25,000 and takes 3–5 weeks. Full strategy-through-build engagements for a defined initiative are scoped and fixed-fee, typically starting at $30,000. Retainer arrangements for ongoing advisory and backlog maintenance start at $5,000/month. We give you a specific estimate after a 30-minute discovery call — no ambiguous hourly ranges or proposals that expand during delivery.
Both — and we think separating them is one of the reasons AI strategy consulting often fails. A strategy produced by people who won't build it tends to ignore implementation reality. We do strategy and implementation with the same team, which means the plan is constrained by what can actually be built, and the build is driven by what will actually create business value. If you just need a strategy, we can do that. If you need the full arc from roadmap to production system, we do that too.
Security is one component of every engagement, not a separate workstream. For regulated industries (healthcare, financial services), we integrate HIPAA, SOC 2, and relevant compliance requirements into the strategy and architecture from the beginning. For organizations taking AI to production, we include security review and threat modeling as part of the production-readiness process. If you need a standalone security assessment or red team exercise for an existing system, we offer that too — but we'd rather help you build it right than audit it after the fact.