Roadmaps that actually ship — not another deck in the drawer.
Most strategy work ends on a slide. Ours ends in a releasable architecture, a costed delivery plan, a named owner for every workstream, and a governance model that survives the first budget cycle.
The patterns we see in every stalled transformation
If any of these sound familiar, the fix is rarely more scope.
The board wants an AI strategy. Nobody owns it.
Pilots proliferate. Use cases compete. Spend is everywhere.
Three years of cloud spend, unclear ROI
Snowflake, Databricks, AWS, Azure — every line item has grown.
Platform decisions are religious, not analytical
Tableau or Power BI? Snowflake or Databricks? Salesforce or ServiceNow? Decisions get made by who shouts loudest, not by what matches the use case.
Strategy decks don't survive the first budget cycle
McKinsey or Accenture delivered a polished roadmap. Twelve months later nothing shipped.
Tech debt is a board-level risk, not a sprint task
Legacy systems are the reason every new initiative adds 30% to timeline. Nobody's quantified the drag. Nobody's sequenced the retirement.
Governance was an afterthought, not a design principle
Data governance, AI governance, platform governance — invented in crisis, not in architecture. Audit findings pile up.
Strategy authored by builders — not handed to one.
Most advisory firms write the deck and hand it to an SI.
- Advisory + delivery, one teamThe partner who designs the target architecture also builds and operates it. No hand-off, no translation loss.
- Outcome-led, not framework-ledWe use frameworks where they accelerate. We drop them where they generalise. Your business, your industry, your cost model.
- Built-in commercial rigorEvery roadmap comes with named owners, costed increments, dependency sequencing, and measurable outcomes by quarter — not a five-year horizon you can't defend.
- Industry-first lensHealthcare, financial services, and Hi-Tech reference architectures — your strategy starts with your industry's reality, not a generic playbook.
Strategy tied to execution
Every phase of strategy & advisory — the 4 A's
A practical framework, engaged where you need it.
Assess
- AI readiness & maturity assessment
- Data landscape & governance audit
- Cloud cost & FinOps assessment
- Application portfolio review
- Technical debt quantification
Architect
- Target-state enterprise architecture
- AI & data platform blueprint
- Cloud strategy (multi-cloud, hybrid, migration)
- Platform selection & rationalisation
- Integration & API architecture
Align
- Governance frameworks (data, AI, platform)
- Operating model & org design
- PMO setup & transformation office
- Change enablement & adoption plan
- Vendor strategy & contract posture
Accelerate
- Sequenced transformation roadmap
- Use-case prioritisation & business case
- Quarterly outcome plan with named owners
- Executive dashboarding & review cadence
- Warm hand-off to delivery (same firm)
A clear strategy execution maturity model
Benchmark where your transformation program is today.
Reactive
Firefighting. Strategy is whatever the last crisis demanded.
Informed
Benchmarks and assessments exist. Leadership agrees on the problem.
Designed
Target architecture documented. Roadmap sequenced. Business cases built.
Aligned
Funding locked. Owners named. Governance running. Quarterly outcomes tracked.
Executing
Strategy and delivery operate as one system. Roadmap self-adjusts on outcomes.
The strategy work we actually deliver
Grounded, costed, and tied to the team that will build it.
| Advisory domain | Primary deliverables | When to engage |
|---|---|---|
| AI Strategy & Readiness | AI maturity score, use-case portfoliogovernance model, 12-month execution roadmap | You're being asked for an AI strategy by the board and need a prioritised, defendable plan — not a pilot list. |
| Cloud & Infrastructure Strategy | Multi-cloud target state, migration planFinOps model, platform rationalisation | Cloud spend is a board-level question. You need a plan that cuts waste and accelerates delivery — together, not in sequence. |
| Data Strategy & Architecture | Data landscape audit, lakehouse designgovernance framework, platform selection | You have Snowflake, Databricks, or Data Cloud and still can't answer basic executive questions. The architecture, not the tool, is the issue. |
| Application Portfolio Strategy | Portfolio rationalisation, modernisation plantech-debt quantification, buy/build/retire recommendations | Too many apps, too many vendors, too much overlap — and any new initiative starts with a month of "how does this work today?" |
| Salesforce & CX Strategy | Org strategy, cloud rationalisationIndustry Cloud readiness, Agentforce adoption plan | Multiple Salesforce orgs, multiple clouds, low adoption — you need a consolidation and value-realisation plan. |
| Platform Selection & Rationalisation | Scored evaluation, reference callsTCO model, consolidation plan | You're choosing between two or three platforms and need a defendable decision — or you have five and need to get to two. |
| Operating Model & Governance | Target operating model, RACIgovernance frameworks, PMO blueprint | Strategy is set but execution keeps stalling — the operating model, not the plan, is the blocker. |
| Transformation Roadmap | Sequenced 12–36 month roadmapnamed owners, quarterly outcomes, funding model | You need a plan that survives the next budget cycle, a steering committee, and an executive turnover. |
Your context isn't generic — neither is our approach
Every advisory engagement starts with your industry's regulatory, data, and cost context.
AI, data, and platform strategy for regulated care
Strategy work that accounts for HIPAA, PHI handling, interoperability.
- AI strategy for payer, provider, pharma
- Data platform rationalisation (Health Cloud + Snowflake)
- Interoperability & FHIR architecture
- Clinical vs. operational AI use-case prioritisation
- Compliance & audit-ready governance
Risk-aware strategy for regulated finance
Cloud, AI, and data strategy that withstands OCC, state insurance.
- AI governance & explainability framework
- Multi-cloud strategy for regulated workloads
- Core system modernisation sequencing
- Advisor & agent platform rationalisation
- Claims, policy, and portfolio architecture
Growth-stage strategy for product-led companies
AI, data, and platform strategy that scales from Series C to enterprise — without slowing product velocity or breaking the culture that got you here.
- AI product strategy & embedded intelligence
- GTM data architecture (product + revenue + CS)
- Platform consolidation pre-IPO
- Public-cloud strategy & cost control
- Scalable governance without startup culture cost
Expert Support That Turns
Technology Into Outcomes
Pre-built IP that compresses months into weeks
Reusable assets that shorten every advisory engagement.
AI Readiness Assessment
2-week diagnostic on data, governance, talent, and use-case depth.
Cloud TCO & FinOps Model
Reference TCO model across AWS, Azure, GCP, Snowflake, and Databricks.
Data Maturity Framework
Proprietary data maturity model across strategy, architecture, governance.
Platform Selection Toolkit
Structured scoring frameworks for BI (Tableau / Power BI / CRM Analytics), data (Snowflake / Databricks), and CX (Salesforce vs. ServiceNow) — with TCO model and reference call guide
Transformation Roadmap Template
12–36 month sequenced roadmap with costed increments, dependency mapping, named owners.
Governance Framework Library
Pre-built governance models for AI, data, platforms, and vendors — policy templates, RACI.
Why leaders choose us over the Big 4 for strategy work
Depth, accountability, skin in the game.
Strategy authored by builders
The team that designs the target architecture is the same team that can build and operate it.
Roadmaps with costed increments
Every deliverable is funded, owned, and tied to a quarterly outcome.
Industry-first, not framework-first
Healthcare, financial services, and Hi-Tech reference architectures — we start with your industry's reality.
Depth across AI, data, cloud, apps
Summit on Salesforce. Services Partner on Snowflake and Databricks. Advanced on AWS.
Commercial honesty
If the right answer is "don't buy that platform," we say so — even when we implement it.
Fixed-scope discovery
Most advisory starts open-ended and ends with an invoice for more scope. Our strategy engagements are fixed scope, fixed-price, and tied to a specific deliverable — so you know exactly what you get before you sign
Credentialed across every platform we deliver on
Partnerships are how we get roadmap access, pre-release enablement, and senior platform engineering on your program.
- Salesforce Summit Consulting Partner
- 1,000+ Customer Success Stories
- 200+ Salesforce Certified Experts
- 100+ Industry Accelerators
- Claude Partner Network
- Claude-powered agents in production across regulated industries
- 40+ enterprise Agentforce deployments grounded on Claude
- Teqfocus runs on Claude — we are our own first client
- AWS Advanced Consulting Partner
- 150+ Active AWS Engagements
- 50+ Skilled Practitioners & Cloud Engineers
- Data & Analytics Competency + 6 Designations
- Snowflake Services Partner
- Expertise in Data Lake to Snowflake
- 50+ Customers across key industries
- 20+ SnowPro Certified Experts
- Certified Databricks Consulting Partner
- 20+ AI & Data Workloads delivered
- 20+ Databricks-Certified Experts
- Expanding focus in Healthcare & Financial Services
Book your strategy discovery session
Start with a 2-week Data Maturity Assessment.
Questions leaders ask before engaging on strategy
Because the same team that writes the strategy can build it. Big 4 advisory typically ends with a deck handed off to an SI — half the original context, half the original architecture intent, all of the original cost. Teqfocus designs the target state and delivers it. The roadmap is honest because we'll have to ship it.
Fixed-scope, 4–8 weeks. Discovery, maturity assessment, target-state architecture, sequenced roadmap, governance model. You leave with a board-ready deck, a costed 12-month execution plan with named owners, and a decision — not a dependency on another engagement.
Often yes — sometimes the answer is a re-baselining. If the roadmap is sequenced and owned, we can move straight to execution. If it's a list of aspirations with no dependency model, we spend 3–4 weeks stress-testing the plan and re-sequencing against reality. Both paths get you to the same honest outcome.
Yes — with deep practices on both sides of every decision. Because we implement every major platform, our evaluations aren't swayed by a single partnership. We score against your use cases, TCO, and operating model, then make a defendable recommendation you can justify to a CFO or the board.
We build governance into the target architecture — not on top of it. Model inventory, risk classification (NIST AI RMF + EU AI Act tiers), evaluation harness, human-in-loop policy, audit logs — all designed during Architect, before code ships. Governance-later is always more expensive than governance-by-design.
Yes — lean, outcome-first, not process-for-process. Teqfocus can stand up a transformation office, quarterly outcome tracking, steering cadence, and executive dashboards. We run it until your team absorbs it. The goal is to dissolve the PMO, not extend it.
The deliverables are yours — and SI-agnostic. Every architecture, roadmap, and governance artifact is documented in a form any implementation partner can pick up. We back the work regardless of who delivers it. Walking in with advisory integrity is the only way advisory work stays honest.
Start with a Strategy & Advisory Discovery. A fixed-scope 2–3 week engagement that frames the problem, identifies the right advisory domain (AI, cloud, data, platform, operating model), and scopes a full engagement. Boardroom-ready whether you continue with Teqfocus or not. Book the discovery.
