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See what I've built

Production AI systems with real numbers attached: LindsAI's multi-agent JIRA and SharePoint automation, GRIT's 50K-session sales enablement platform, voice-to-SQL copilots, and more. Each one had to survive daily use by a real team.

Enterprise AI deployments

Case studies where the system had to help a real team.

What they have in common

Every system here started from a clear user task, shipped with metrics tied to adoption or efficiency, and held up under daily production use.

Clear user taskMeasurable impactSurvives daily use
Workflow Automation01

LindsAI

Multi-agent automation with JIRA, SharePoint & live web search

98%
intent accuracy
<10 min
intake to ticket
View case studyLangGraph +3
Revenue Enablement02

GRIT

Adaptive sales enablement for regulated medical teams

65%
faster onboarding
50K+
monthly sessions
View case studyRAG +3
Voice Workflow03

Talksmith

Voice-first analytics for teams that live in data

200+
daily users
8
business teams
View case studyLangGraph +3
Interview Prep04

IntervueRecall

Interview recordings turned into clean question lists

1-click
audio upload
Qs
extracted list
View case studyAudio Transcription +3
Knowledge Copilot05

InsightDesk AI

A knowledge copilot for documents, tables, and daily decisions

10K+
monthly questions
~50%
analyst lift
View case studyDatabricks +3
Content Operations06

LinkedInfluencer

AI content intelligence for building a credible LinkedIn voice

20+ hrs
saved weekly
A/B
content optimization
View case studyLangGraph +3
Talent Screening07

FitScout

Recruiter intelligence for faster resume screening

1000+
resumes monthly
90%+
screening accuracy
View case studyLlamaIndex +3
Legal Ops08

WhisperIt Legal Copilot

A private document assistant for faster legal review workflows

45%
faster turnaround
GDPR
privacy aligned
View case studyRAG +3
Shared Services09

OpsAnswer Hub

One assistant for HR, finance, policy, and payroll questions

40%
routine query share
200+ hrs
saved monthly
View case studyLangChain +3