Project Overview
Strategy & Advisory
AI Products & Platforms
Agents
Knowledge Systems
Governance & Risk
A global management consulting firm partnered with SFAI Labs to enhance how large organizations act on employee survey and 360 assessment data. While the firm had strong advisory capabilities, scaling personalized, actionable guidance to thousands of managers required a robust AI-driven solution.
SFAI Labs worked closely with consulting leadership and delivery teams to design and build an embedded AI assistant that translates complex workforce data into practical coaching and action plans. The engagement focused on aligning consulting methodologies, technical architecture, and enterprise delivery standards.
Within ten weeks, SFAI Labs designed, engineered, and validated a production-ready AI assistant integrated into the firm’s client delivery workflow. The system combined structured data ingestion, contextual reasoning, and policy guardrails to ensure reliable, compliant, and scalable deployment.
The result was a fully functional AI coaching platform that amplifies consultant impact, improves client outcomes, and strengthens the firm’s competitive differentiation in enterprise engagements.
Key Takeaways
AI amplifies consulting impact
Embedded systems drive adoption
Evaluation ensures reliability
Guardrails enable trust
Scalable design supports growth
Challenge
The client supported large enterprises in interpreting employee survey and assessment data and translating insights into leadership actions. This process relied heavily on manual analysis, report interpretation, and consultant-led workshops. Scaling personalized guidance across thousands of managers created operational bottlenecks and inconsistent quality.
Early AI experiments lacked sufficient context awareness, governance controls, and alignment with consulting methodologies. The firm required a system that could operate at enterprise scale while preserving trust, compliance, and professional standards.
Strategy
SFAI Labs defined a build-first strategy centered on embedding AI directly into the consulting delivery model. We aligned system design with advisory frameworks, defined quality benchmarks, and established an evaluation-driven development loop.
The strategy emphasized:
Deep integration with internal data systems
Structured knowledge ingestion and retrieval
Continuous measurement of relevance and faithfulness
Strong governance and deployment controls
A user experience focused on action and coaching
Solution
We designed and built an enterprise AI assistant platform featuring:
Secure ingestion of survey and performance data
Contextual retrieval across multi-year datasets
Role-based access and persona management
Action-oriented coaching responses
Built-in policy enforcement and safety layers
Export and reporting capabilities for consultants and clients
The assistant functions as a digital coach, guiding managers through interpretation, root-cause analysis, and structured action planning while maintaining alignment with consulting best practices.
Execution
Week 1–2: Consulting workflow mapping and system architecture design
Week 3–4: Data integration and knowledge ingestion pipelines
Week 5–6: AI assistant development and baseline evaluation
Week 7–8: Policy tuning, guardrails, and usability iteration
Week 9–10: QA hardening, security review, and deployment readiness
Results
Context relevancy improved by ~45%
Positive user ratings more than doubled
Policy violations reduced by over 85%
Business Value
The engagement enabled the firm to deliver consistent, high-quality coaching at scale while reducing manual analysis effort. The AI assistant increased consultant leverage, improved client satisfaction, and strengthened the firm’s ability to win and retain enterprise accounts through differentiated digital delivery.
Why SFAI Labs
SFAI Labs combines AI Product Strategy with hands-on engineering and governance expertise. Our lab model enabled the rapid design, build, validation, and deployment of a production-grade AI system aligned with consulting workflows and commercial objectives.
