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Generative AI

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PROCESS AIRWORTHINESS & MAINTENANCE DATA FASTER FOR COMMERCIAL INSIGHTS

KeepFlying's Generative & Predictive AI gets your datasets LLM ready to generate
ROI across your business needs.

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Trusted by 10,000+ companies around the world



CURRENT LANDSCAPE


POWERFUL FEATURES TO HELP YOU CLOSE SALES FASTER.

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AIRLINES SPEND OVER USD 2 MILLION PER NARROW BODY REDELIVERY


ENGINE MROS MISS OUT ON OVER USD 250,000 IN BOTTOM LINE PER ENGINE OVERHAUL


LESSORS SPEND OVER USD 50,000 PER AIRCRAFT OR ENGINE RECORDS INSPECTION




AI AGENTS DRIVEN USE CASES POWERED BY

SkyBot, MROBot & LeaseBot

Engines
Airframe
Scrap Rate Predictor


SCRAP RATE PREDICTOR


What?
Predicting which components will be scrapped in the Next Maintenance Visit
necessitates a clear understanding of the varying complications in an Engine's
history, spanning multiple operators, environments, thrust ratings, and
maintenance visits, and the respective weightage assigned to each technical,
operational, and environmental variable.
Why?
Accurate prediction of scrap rates enables the implementation of procurement
plans to ensure part availability during repair, mitigating delays in
procurement timelines and turn-around times, given that often, during repair and
inspection, the determination of parts needing repair versus those needing scrap
and replacement only becomes apparent.
How?
Our algorithms analyze the behavioral profile of each Engine Serial Number (ESN)
by integrating its operational, technical, and environmental parameters to
predict scrap rates for each component, incorporating weightage assigned to each
parameter, relationships between parameters, and a confidence interval to
support prediction accuracy.

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Shop Visit Profiler


SHOP VISIT PROFILER


What?
For Operators or Lessors managing a fleet of Engines at different ages and
stages, strategic planning and profiling of Engine Shop Visits are crucial to
maximize modular lifespans, conserve cash, and design optimal build goals
aligned with overall cash flow objectives.
Why?
Effectively managing a diverse fleet of engines at various lifecycle stages and
statuses (In Operation, Shop Visit, Storage) necessitates Lessors or Operators
to optimize the residual lives of modules and LLPs as the fleet matures,
involving profiling Shop Visits against individual Engines or fleets to analyze
statuses, potential module swaps or exchanges within the fleet for cost
conservation, and facilitating immediate lease placements to enhance the value
and utilization of each Engine.
How?
KeepFlying® algorithms evaluate fleet statuses, predicted scrap rates, work
scope levels, and residual lives across modules to compute the commercial impact
of build goals, swaps, and exchanges, facilitating the profiling of shop visit
costs and placements to optimize profitability and minimize expenses.

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Work Scope Predictor


WORK SCOPE PREDICTOR


What?
An Engine's diverse operational history, spanning different operators,
environments, thrust ratings, and maintenance visits, presents varying
challenges in predicting repair work scope levels for its modules during the
upcoming Maintenance Visit to enable Engine Operators and Lessors to effectively
plan and budget for associated costs.
Why?
The capability to forecast repair work scope levels aligned with Engine Build
Goals empowers Operators and Lessors to opt for cash conservation and simulate
maintenance economics, or in the case of an engine undergoing lease transition,
enables them to budget and strategize maintenance to ensure swift turn-around
time and smooth transition to the new Operator.
How?
Our algorithms, trained on datasets integrating an Engine's Maintenance and
Operational history, analyze and correlate the impact to predict repair work
scope levels for each module prior to a visit, often preempting necessary
upgrades during module split and strip inspections, facilitating proactive
commercial planning and minimizing turn-around time.

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Trade Off Maintenance Vs Fuel Consumption


TRADE OFF MAINTENANCE VS FUEL CONSUMPTION


What?
The decision to delay maintenance on a mid-life or aging Engine results in
increased fuel consumption and expensive shop visit costs, posing challenges in
justifying Engine Shop Visits without residual values or clear revenue
visibility from usage or lease placements, necessitating a careful trade-off
between timely maintenance visits and ongoing fuel expenses.
Why?
Operators must weigh the increasing fuel consumption of mid-life and aging
engines against the cost of sending them for a Shop Visit, considering the
significantly improved fuel efficiency of next-generation engines, thus
necessitating a trade-off decision.
How?
By incorporating the Engine's past shop visit records, removal causes, and
predicted scrap rates, our algorithms compute EGTM deterioration profiles and
ongoing fuel costs, juxtaposing them with potential revenue streams; the
resultant savings from scheduling a Shop Visit not only enhance customer
satisfaction but also ensure prolonged engine availability.

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Slot Profitability Forecaster


SLOT PROFITABILITY FORECASTER


What?
Maintaining the commercial viability of slot sales in fixed-price Engine
Maintenance contracts necessitates tracking and predicting Engine Cost Build up
before and during Engine Induction, ensuring adherence to slot profitability
targets.
Why?
Predicting variances in Engine Cost Build up early is crucial for mitigating
risks associated with the escalation of work scope levels, upgrades of repairs
to replacements, and scrapping of components not covered as part of fixed-price
elements, thereby safeguarding profitability of an Engine Shop Visit and
preventing adverse impacts on the shop floor.
How?
Our algorithms activate work scope escalation and scrap prediction functions in
coordination with capacity constraints to ensure Engine slots meet contracted
turnaround times and target profitability, facilitated by dynamic capacity
balancing models that assess the impact of scraps, replacements, swaps,
exchanges, and repairs on timely Engine turnaround and associated costs to
predict slot profitability.

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Gate 0 Profiler


GATE 0 PROFILER


What?
Upon Engine MROs receiving Engines into the shop, digital documents arrive in
diverse unstructured formats, with the Engineering team typically requiring
three weeks to process these incoming documents and devise a shop floor plan.
Why?
Engineering teams must examine the incoming Engine documents from the Lessor or
Operator to evaluate any fluctuations in work scope levels and scrap rates
against components, thereby ensuring preparedness of the Shop Floor and
Procurement teams with the necessary labor and material capacity to meet
contractual obligations within the turnaround time.
How?
By combining smart asset type driven OCR with ATA Spec2500-driven standards, our
algorithms interpret incoming Engine documents, potentially reducing processing
time for Engineering teams from three weeks to a few days.

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Contract Stress Tester


CONTRACT STRESS TESTER


What?
Engine MROs engage in negotiating fixed-price contracts with Operators and
Lessors to enhance their bid-winning prospects, though they face the risk
associated with varying levels of repair work scopes required for engines and
the MRO's capacity to meet demand within contracted turnaround times.
Why?
Engine MROs strive to optimize their capacity utilization across fixed-price
LTAs with Operators, Lessors, OEMs, while also accommodating capacity for time
and material-driven hospital visits to maximize profitability, necessitating
thorough stress testing of fixed-price contract slots before committing to terms
and conditions related to repairs, materials, scraps, and labor.
How?
Our algorithms conduct Shop Visit lifecycle simulations, ranging from slot
prospecting to induction, utilizing either a limited or exhaustive set of
parameters against an Engine Serial Number (ESN) to rigorously evaluate fixed
price elements concerning work scope levels, scrap limits, material, and labor
caps, allowing for multiple simulations to be conducted prior to finalizing
contract terms and conditions.

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Gates 1-4 Tracker


GATES 1-4 TRACKER


What?
Tracking planned versus projected Shop Visit progress once the Engine is in shop
is critical to manage aspects of disposition, kitting, and dependencies on
external repair vendors and suppliers that may impact TAT, while predicting
repairs that may upgrade to a replacement or material risks owing to vendor
performance poses a challenging task.
Why?
Tracking and mitigating gate-wise risks is crucial once a fleet of engines is in
the shop to ensure all engines are returned within contracted Turnaround
Time(TAT), and in case of delays, providing risk mitigation avenues is essential
to uphold overall profitability.
How?
Our algorithms assess engine status, monitor cost accumulation, and forecast
deviations to assess risk mitigation strategies, leveraging vendor performance
ratings to recommend potential repairs, swaps, and exchanges to optimize TAT
savings and prioritize ESNs for scheduling algorithms aimed at achieving the
optimal balance between TAT and profitability.

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Records Copilot


RECORDS COPILOT


What?
Aircraft and maintenance records, which can exist across various systems
including Records Management Systems, Content Management Systems, and MRO
Software Systems, are typically unstructured and can be found in PDF, Excel, or
CSV formats.
Why?
Interpreting Aircraft and Maintenance Records from diverse unstructured sources
involves context-based analysis beyond OCR, enabling faster decision-making,
while resolving duplicate or conflicting data sources for coherence. 
How?
Our records interpretation platform provides a ChatGPT "like" interface that
offers users to efficiently query and retrieve relevant information from
back-to-birth records through natural language conversations.

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Aircraft Transition Economics Monitor


AIRCRAFT TRANSITION ECONOMICS MONITOR


What?
During a lease transition, obtaining access to all aircraft technical records is
essential, especially for older aircraft with multiple previous operators, as
assembling complete records spanning the aircraft's entire history can be
difficult.
Why?
Identifying critical data, such as for back-to-birth tracing of life-limited
components or modifications that need to be carried out in concurrence with new
lessee's requirements, amidst this vast repository can be particularly
challenging. Arriving at cost estimates for this transition can become a
time-consuming process.
How?
Enabled by the Records Co Pilot feature, this function facilitates Lessors and
Airlines in appraising and estimating transition efforts and expenses during the
transfer of an Aircraft between lessees, assessing costs associated with
bridging programs and modifications necessary for transitioning the aircraft
from its current state to a "to-be-delivered" status by examining records and
conditions.

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Automatic Redelivery Binder Generator


AUTOMATIC REDELIVERY BINDER GENERATOR


What?
During aircraft redeliveries, the return conditions outline how the previous
lessee is expected to redeliver the aircraft, while the delivery conditions
specify how the aircraft should be presented to the next lessee. Ideally, these
conditions would align perfectly, but in reality, such alignment is rare.
Why?
The timeframe between transitions and the potential consequences of redelivery
violations can impact both lessees and lessors significantly. Initiating this
process 12-18 months prior to redelivery is crucial to facilitate a seamless
aircraft transition and to identify avenues for mitigating risks, ensuring a
trouble-free redelivery experience.
How?
The function streamlines risk mitigation and cost escalation calculations for
Aircraft Redeliveries, with the Records Co Pilot tool aiding in rapid
interpretation of records and redelivery conditions, while algorithms forecast
statuses and identify avenues for risk reduction to facilitate cost savings,
binder generation, and ensure a smooth transition.

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ATA SpXchange


ATA SPXCHANGE


What?
Aircraft technical and maintenance records, generated from various systems and
formats, undergo exchange in diverse formats when aircraft transition between
lessees, redelivered to a lessor and delivered to another lessee, or return from
maintenance visits.
Why?
The Air Transport Association (ATA) has established standards for data exchange
within the aviation ecosystem, facilitating seamless transfer of records by
defining specifications for aircraft records, configuration, ARCs, eTech logs,
maintenance summaries, reliability, and supply chain data.
How?
The KeepFlying® SpXchange ATA Specification Platform is a modularized approach
to each ATA Specification. It provides the necessary tools to wrangle data that
is not in an ATA Specification and output that data in the appropriate ATA
Specification. This can then be further integrated in to or interrogated by
down-stream systems removing the need for expensive or time-consuming human
data-capture processes.

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AVAILABLE AS

For MRO's

For Airlines & Lessors


HOW WE DO IT?




START YOUR DSAAS JOURNEY TODAY!

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OUR PLATFORM.


FINTWIN®

Allows Airlines, MROs, Lessors & Financiers to run "what-if" scenarios to
simulate commercial impact of decisions against Assets and Maintenance Visits


ATA SPXCHANGE

Extracts & converts 100% of technical PDF content into a Machine-Readable
data-structure. This is proven to enable faster data-consumption.


DATA WRANGLER

Ensures airworthiness and maintenance data integrity by integrating diverse
sources into a unified, accurate view, enhancing decision-making and operational
efficiencies.


SKYBOT™

Aviation-specific LLM-powered chatbot (integrated with FinTwin® platform),
designed to effortlessly query large datasets and extract vital information.




START USING THE CRM PLATFORM OF THE FUTURE, TODAY.

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CREATE YOUR ACCOUNT TODAY.

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1. CREATE YOUR ACCOUNT



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2. INTEGRATE WITH YOUR TOOLS

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3. CLOSE MORE SALES



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DESIGNED FOR ALL KIND OF TEAMS.


SALES TEAMS

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MARKETING TEAMS

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SUPPORT TEAMS

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100 Tras Street #09-01 100AM, Singapore 079027

15-16, 64-66 Bannister Road, Canning Vale, Western Australia 6155

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