Agentic AI Doubles AI Adoption and Cuts Cost Overruns by 20% for a Global Engineering Firm
Client Overview
A global engineering and consulting firm delivers infrastructure, environmental, energy, and transportation programs for public and private sector clients. Its partnership with Indium began in 2019 with Deed-Plotter and grew into a strategic AI charter spanning eight capability areas. Business teams still relied on manual document reviews, while growing AI adoption made tool access and cost tracking harder to manage. The client set out to move AI from early pilots to measurable business outcomes at scale.
Manual Workflow and Scattered Knowledge Slowed Daily Operations
The client’s AI charter kept growing and so did the pressure to prove its value. Nine operational areas slowed that progress and affected the everyday work across business teams.
01
Scattered Enterprise Data and Meeting Insights
Teams struggled to access and consolidate enterprise data, meeting insights, Excel-based information, and user feedback. Actionable follow-ups took more effort to produce.
02
Manual and Fragmented RFP Handling
Proposal teams processed RFPs and generated proposals through manual, fragmented steps, and compliance checks followed the same pattern. Speed and consistency suffered, and the process became harder to scale.
03
Manual Document Processing
Manual extraction, validation, scraping, and communication steps created inefficiencies and lengthened turnaround time.
04
Hard-to-Reach Standards and Knowledge
Engineers struggled to access and accurately reference extensive standards and technical documentation. Collaboration around those documents proved difficult as well.
05
Time-Consuming Site Planning
Site planners handled georeferencing and metadata extraction manually and compared layouts by hand. Site planning and compliance work became time-consuming.
06
Limited Energy Data and Recommendations
Limited access to integrated energy data and tailored recommendations hindered efforts to optimize consumption and reduce operational costs.
07
Limited AI Cost and Token Visibility
CXO-level leaders needed a centralized view of AI token consumption and cost, and visibility stayed limited.
08
Difficult AI Application Discovery
A growing number of AI applications and dispersed access points made it difficult for users to discover and reach the right tool.
09
AI Evaluation and Governance
Governance became harder because AI solutions needed evaluation across bias, PII, accuracy, and security under a standardized framework.
Domain-Tuned Agentic AI for Business Teams
Indium partnered with the client as a consultation partner, starting with tactical pilots and growing into an enterprise-wide partnership. Domain-specific AI paired the firm’s knowledge with workflow automation, so teams could act on information that used to sit in separate places.
01
Document Processing POCs
Tactical POCs around document processing gave the client a working footprint. The results validated the capability and opened the way to pilot expansion.
02
Purpose-Built Pilots
Pilots such as WiseGPT gave employees an enterprise chat with internal and external web search across multimodal inputs.
03
Multi-LOB GenAI Delivery
Contextual models and RAG workflows, backed by improved data quality pipelines, took GenAI across multiple lines of business.
04
Domain-Tuned Agents
GenAI applications now serve engineering, energy, grants, and geospatial teams. They cover site mapping, RFP analysis, advisory services, and domain chat.
05
Governance & Guardrails
Human-in-the-loop review, confidence scoring, PII masking, and content filtering through Azure OpenAI keep every application accountable. Evaluation frameworks and model monitoring track accuracy and hallucinations.
06
AI Embedded in Delivery
AI now runs inside the client's PDLC, DataOps, and Assurance work. It builds an AI-first culture and keeps the roadmap moving.
Everyday AI Brings Faster Turnaround and Lower Costs
WiseGPT: Employee AI Assistant
Employees search company knowledge and the web for answers right inside Microsoft Teams.
- 30% fewer queries landing on domain portals
- 74% faster task completion
RFP Analyzer: Proposal Intelligent Solution
Proposal teams analyze RFPs and draft responses in one place, with compliance checks built in.
- 11% higher win rate
- 400+ pages analyzed in 1 minute
- 25% faster turnaround
Funding 360: Grant Tracking
Teams find and track grants in Salesforce and stakeholder updates go out automatically.
- About 100 grants are handled automatically
- 35% less time spent on review
AI Design: Engineering Standards Search
Engineers find the right standard and technical document in one place and design solutions faster.
- 95% citation accuracy for engineers
- 90% efficiency from a shared knowledge source
GeoPlotter: Site Mapping from Documents
Engineering documents turn into GIS-ready maps through automated parsing and positioning.
- 24x less effort per person
- 97% of generated maps worked with GIS software
Energy Advisor: Tailored Efficiency Advice
Personalized recommendations show where to cut consumption and improve operational efficiency.
- 30% rise in the renewable adoption forecast
- 25+ active users
AI Dashboard: Usage and Cost Tracking
Leaders see how people use each AI application and what it costs, all in one view.
- 20% drop in unexpected cost overruns
- 10% lower operating costs
AI Hive: Internal AI App Store
Employees discover and open the AI applications their role allows, all from one store.
- 2x higher adoption and access to all AI apps
AI Trust Framework: Quality Checks
The framework checks AI applications against verified answers and monitors output quality over time.
- AI solutions assessed with 85% efficiency
Digital Backbone
Business Teams Gave AI a Clear Purpose
The firm’s AI journey grew through use cases identified by the people doing the work. Employees brought operational problems forward, and business and IT teams worked together to address them. As adoption expanded, shared governance gave teams a consistent way to evaluate applications. The firm established a practical pathway for transforming employee ideas into AI applications that deliver measurable business value, while building a strong foundation to sustain and scale its AI journey into the future.