Lighty — AI Opportunity Discovery

What took four months
now takes twenty-four hours.

Traditional process analysis means months of workshops, consultants, and spreadsheets before you see a single insight.

Lighty connects your Slack, email, and ERP data to surface the invisible workflows between your systems: the approvals, escalations, and handoffs that no system of record captures. The result is a prioritized map of AI opportunities, delivered Monday.

A structured sprint from
data to decisions.

No lengthy engagements. No black-box output. A deliberate five-day process that gives your team a clear picture of where AI creates the most value, and why.

01

Connect your data sources

Share Slack exports, email archives, or structured ERP data. Lighty reads both the systems of record and the human communication between them: the full picture of how work actually moves.

Slack Email SAP / ERP Zendesk Calendar

02

Causal discovery across systems

Our engine maps the invisible workflows: the approvals, handoffs, and escalations that live between structured transactions and unstructured conversation. Not what your process charts say happens. What actually does.

Causal analysis Pattern discovery Bottleneck detection

03

Prioritized AI opportunities

You receive a ranked list of opportunities with root cause analysis, ROI estimates, and quick-win recommendations, ready for your leadership team on Monday morning.

ROI estimates Root cause analysis Executive readout

Platform

Four steps from raw data
to clear decisions.

The Lighty platform connects your existing systems, identifies the workflows between them, and produces a ranked map of where AI creates measurable value, delivered in days, not months.

Step 01

Data Ingestion

Emails, documents, APIs, databases, and enterprise systems are seamlessly integrated: structured and unstructured alike.

Slack Email ERP / SAP Zendesk

Step 02

AI Analysis

Our LLM identifies patterns and extracts workflow structures with semantic understanding across your full data landscape.

Pattern recognition Semantic understanding Sequence mapping

Step 03

Workflow Mapping

Interactive visualization of actual processes and bottlenecks, not the documentation, but what actually happens day-to-day.

Causal DAG Bottleneck detection Root cause

Step 04

Smart Recommendations

Actionable insights with prioritized recommendations, ranked by ROI, urgency, and feasibility for your leadership team.

ROI estimates Executive readout Quick wins

app.lighty.ai/analysis/ap-invoice-cycle

Export

Run Analysis

Summary

Graph

Optimize

Causality

Data

47,312

Invoices analyzed

$1.8M

Recoverable capacity

31%

Approval delay rate

3

Critical bottlenecks

Workflow Map

Invoice Received

→

PO Matching

→

Approval Routing3.2d avg

→

Payment Release

→

Reconciliation

Causal analysis traces 68% of payment delays to sequential approval routing. Parallel routing could recover 2.1 weeks per cycle.

AI Recommendations

Automate PO Matching

$840K

94% of invoices match PO data deterministically. Full automation eliminates the manual review queue.

Parallel Approval Routing

68% faster

Sequential approval adds 3.2 days per invoice. Parallel routing with threshold rules eliminates the bottleneck.

Duplicate Detection

12.3% reduction

1 in 8 invoices triggers a duplicate flag. Pattern-matched auto-resolution removes manual triage.

Use cases

Built for the workflows that
move money.

Insurance operations

Claims, onboarding, policy servicing

Surface bottlenecks in the processes that matter most: where delays cost the most and manual work is most replaceable.

Insurance client: Identified recoverable capacity across a $400–500M transformation program. Delivered in advance of a stage-gate presentation to program leadership.

PE portfolio operations

Value creation across portcos

Give operating partners instant visibility into portfolio company workflows. The 5-Day Sprint was built for PE firms running parallel value creation programs.

PE portfolio company: Mapped CS and AP workflows across 10 legacy ERPs, surfacing automation opportunities in a 90K invoice-per-year operation.

Consulting-led diagnostics

Accelerate your client engagements

Consulting partners use Lighty to run AI opportunity diagnostics at scale, with white-label results and branded deliverables ready to present.

Active partner program: Lighty accelerates the diagnostic phase of enterprise transformation engagements for major consulting practices.

Sales & revenue operations

Where deals slow down and why

Identify the exact communication patterns that separate won deals from lost ones, and the workflow friction that adds weeks to your sales cycle.

B2B lender: Analyzed 17,000 emails to surface the root cause behind a 12.6% close rate and the specific bottlenecks adding 45 days to deal cycles.

Case studies

Work that speaks
for itself.

Case study 01

Hiring operations

5

Business days removed
from time-to-hire

Minutes

Candidate scheduling time
(down from 1.5 days)

A slow hiring process
was losing top candidates.

A tech firm's hiring process had consistent 3-day delays at every stage. A high-priority candidate accepted another offer while the team was still moving through internal approvals.

Lighty analyzed emails, Slack, and calendar data to map the actual hiring workflow, not the documented one. The bottlenecks were invisible in any single system but unmistakable across all three.

Outcome: The client implemented a priority workflow for high-value candidates and deployed Lighty's scheduling assistant to eliminate bottlenecks. Candidate scheduling went from a multi-day process to minutes.

Case study 02

Academic operations

27%

Improvement in
student satisfaction

40%

Reduction in
meeting time

Disorganized coordination was costing everyone.

A construction management course at a major university had a recurring problem: student project teams were missing deadlines, duplicating work, and escalating confusion to faculty instead of resolving it internally.

Lighty developed specialized coordination tooling to clarify ownership and surface action items before they became delays. The result was transparent workflows and clear accountability at every project phase.

Outcome: Student satisfaction scores improved significantly, redundant follow-up communications declined, and team meetings became shorter and more productive with clear agendas and trackable outcomes.

Case study 03

Marketing operations

18%

Increase in
lead conversion rate

30%

Reduction in campaign
development time

A B2B team couldn't see
what was actually working.

A marketing team had years of campaign data but no reliable way to understand what was driving results. Resource allocation was based on intuition. ROI was difficult to demonstrate to stakeholders.

Lighty analyzed historical creative assets and messaging patterns across campaigns, surfacing the specific combinations that correlated with high-converting outreach. The patterns were actionable and specific enough to change direction immediately.

Outcome: The team implemented data-driven decisions across messaging strategy, creative direction, and channel selection. Lead conversion improved 18% and campaign development time dropped by nearly a third.

Case study 04

Telecom operations

62%

Reduction in mean time
to detection (MTTD)

3.1×

Faster mean time
to resolution (MTTR)

A telecom operator couldn't see
why tickets kept escalating.

A major telecom provider had tens of thousands of unified trouble tickets (UTT) flowing through their support organization each year. Resolution times were unpredictable, escalation rates were high, and the root causes were buried across multiple systems.

Lighty applied causal discovery across the full ticket dataset, mapping the actual chain of events from detection to resolution, surfacing the specific workflow patterns that were driving delays. The causal DAG identified bottlenecks that no individual system could see on its own.

Outcome: The engagement produced a prioritized intervention map across the support workflow, enabling faster detection, clearer escalation routing, and a measurable reduction in resolution time across the affected ticket categories.

Team

Built by people who've
done it before.

The Lighty founders met at MIT and have spent decades building products at scale at companies like Google, Twitter, and GIPHY. They're experienced founders, operators, and AI researchers with a combined five exits and four patents.

Co-founder, CEO

Richard Rabbat

PhD from MIT Media Lab. Previously VP Product at Twitter, where he led product strategy across multiple core surfaces. Founded Gfycat, the short-form video platform, and led it through acquisition by Snap.

MIT PhD Twitter VP Product Gfycat → Snap

Co-founder, CTO

Anthony Johnson

MIT B.S. CS and M.S. Media Technology. Ex-CTO of GIPHY, where he scaled the platform to 100 billion API requests per month before its acquisition by Facebook. Previously CTO of Thrasio. Five successful exits. Four patents at Lighty.

MIT CS GIPHY CTO → Meta 5 exits 4 patents

Co-founder, COO

Mikey Kindler

Harvard MBA, MIT undergrad. Previously a Director at Google AI, where he led product and strategy across AI initiatives. Brings deep operational and commercial expertise to Lighty's go-to-market and partnerships.

MIT + Harvard MBA Google AI Director

Join our team.

We're looking for people who want to work on genuinely hard problems at the intersection of AI, data, and enterprise operations. If that's you, we'd like to hear from you.

Get in touch

See your AI
opportunities.

Request a demo and we'll show you what Lighty finds in a workflow similar to yours, before you share a single piece of data.

Response within one business day

Data Friday, insights Monday

NDA available before any data sharing

Currently in private beta, limited availability

What took four monthsnow takes twenty-four hours.

A structured sprint fromdata to decisions.