Scaling Smarter: How One Market Intelligence Firm Used AI to Accelerate Research, Proposals, and Client Delivery
A behind-the-scenes look at how a fast-moving team drove results without adding headcount
This is the final post in our five-part series on how AI is transforming market intelligence firms. We’ve explored how AI supports business development, knowledge management, and client delivery. Now, we’ll take you behind the scenes of a real firm that put it all together — and what happened next.
The Challenge: More Work, Higher Expectations, Limited Bandwidth
This mid-sized market intelligence firm supports global clients in energy, finance, and mobility. Known for high-quality insights and fast turnaround, the team was facing pressure to scale delivery without increasing headcount.
The friction points were familiar:
- Analysts were recreating work because prior research was hard to find
- Proposal teams spent nights and weekends building decks from scratch
- Consultants were handling client follow-ups manually — summaries, slides, data pulls
- Client data security made public AI tools off-limits
The team needed a way to move faster without compromising quality, consistency, or control.
The Solution: Embedded AI, Purpose-Built for Knowledge Work
Instead of overhauling their systems, the firm deployed private AI agents inside their existing SharePoint, Teams, and CRM environment.
These agents were trained to:
- Retrieve insights from thousands of past reports, presentations, and transcripts
- Generate proposal drafts tailored to industry, scope, and prior wins
- Support clients directly via a secure, white-labeled portal — answering questions and surfacing insights on demand
The firm didn’t need a new platform or AI team. Agami fit right into their workflows, with no data leaving their environment.
The Results: Faster Research, Smarter Proposals, Better Client Experience
In just a few weeks, the impact was measurable:
- Research briefs that once took 2 to 3 days were created in a few hours
- Proposal turnaround time dropped by over 60 percent
- Analyst bandwidth expanded — creating room for 2 additional projects per quarter
- Client follow-ups were handled 30 percent faster, with AI answering repeat questions
- Payback period: Under 3 months
- ROI: 4x in the first 6 months
"Now, my first step is just asking a question. I easily save an hour a day and get to the actual analysis faster."
— Senior Analyst
What Made This Work
This wasn’t a flashy AI experiment. It was a focused, secure deployment designed to support real workflows:
- Private by design — no client data left the firm’s control
- Trained on internal content — not generic internet data
- No workflow disruption — analysts didn’t have to learn new tools
- Deployed in weeks — not quarters
Leadership was clear: the goal wasn’t to use AI for the sake of it. The goal was to empower analysts, protect client trust, and deliver faster.
See the Full Case Study
Want to see how they implemented AI across research, proposals, and client engagement?
Download the full case study to get:
- Specific use cases by role and function
- A week-by-week deployment timeline
- Before-and-after comparisons across KPIs
- Lessons learned by leadership and analysts
- ROI breakdown from the first 6 months
Bring This to Your Firm
If you’re facing growing demand, rising client expectations, and tighter delivery timelines — without more bandwidth — this story is worth a closer look.
Book a demo to explore how Agami supports scalable growth
