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Open-source intelligence · Strategic research · Decision analysis
Spot the pattern early, price the exposure, and plan your move with evidence.
ConsultKitApp is an independent research practice built for shipping, energy, finance, and investment teams. We gather intelligence from public sources and test it using mathematical optimization, simulation, and carefully verified AI. Instead of a pile of news clippings, you receive a structured decision brief: every fact is sourced and dated, every risk is quantified where data permits, and every remaining unknown is stated plainly.
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How the work is done
CURRENTLY ACCEPTING NEW ENGAGEMENTS · REPLIES WITHIN ONE BUSINESS DAY
SIGNAL FIELD — ILLUSTRATIVE
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internal reference dossiers and sector studies compiled covering companies and corridors across the Gulf, Singapore, Hong Kong, and the Arctic
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decision variables in our benchmark disruption-recovery model, solved to mathematical optimality and verified line by line
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constraints in the same benchmark model — accounting for capacity limits, inventory balances, and operational rules simultaneously
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starting fee for standard research engagements. Rigorous verification and custom modeling require dedicated analyst time
War-risk cover for the Persian Gulf suspended by five insurance clubs · Mar 2026 confirmed
Transit insurance at Hormuz reached 7.5–10% of hull value corroborated
Container war-risk surcharge on affected lanes ≈ $1,500 per box corroborated
VLCC, Middle East–China: ≈ $12M for a single voyage corroborated
Northern Sea Route transit verified at 20–22 days confirmed
Geopolitical risk ranked the top CEO concern going into 2025 reported
Northern route transit “down from 40 days to 20” · market commentary reported
“The strait remains open” · 7 July wire superseded
§ 01 — What the fee buys
Three commitments in every research file.
Our practice is designed for shipping and logistics desks, energy and trading houses, banks, insurers, and investment teams facing operational or counterparty uncertainty. Whatever the subject, every report we produce is built on three practical standards.
01
Checked facts, dated sources
Every factual statement in a report cites its source and date. When new information contradicts earlier reports, both remain in the source ledger with a clear note on what changed and when. You always have a complete audit trail showing how the facts evolved.
02
Quantified trade-offs
Where data allows, we express risk as cost, probability, and break-even thresholds so you can compare options directly. Calling a risk “elevated” doesn’t help you build a budget; knowing that transit insurance has reached 9% of hull value does. Whenever a trade-off can be calculated responsibly, we calculate it.
03
Clear boundaries on what is known
When public evidence runs out, the report tells you exactly what is missing. You always know which conclusions rest on verified data and which rely on analytical judgment or modeling assumptions. Identifying an information gap upfront is far safer than acting on an unexamined guess.
The sections below outline our verification workflow, our standard engagement formats, and an interactive route-comparison model you can test yourself.
§ 02 — Method · how the work is done
Three phases, two quality checks, full traceability.
Every research file follows a structured three-stage workflow. We do not move to the next phase until the current one passes a strict quality check, and every claim in the final document is tagged by how thoroughly it has been verified.
PHASE 1 · VERIFICATION
We gather relevant public records, filings, and trade reporting, and cross-check each claim. Every statement is linked to a dated source. When newer reporting contradicts older data, we log the update so the timeline stays clear. Claims that cannot be independently verified are explicitly recorded as open data gaps.
CHECK 1 → 2 — all material claims verified or logged as explicit data gaps
PHASE 2 · ASSESSMENT
Once the baseline facts are established, we map the key actors, operational exposures, plausible scenarios, and early-warning indicators. If a route or commercial option is no longer practical under current conditions, we rule it out early so you don’t waste time evaluating dead ends.
CHECK 2 → 3 — scenarios defined, early indicators selected, decision trade-offs framed
PHASE 3 · QUANTIFICATION
Finally, we run the quantitative analysis: optimization models, scenario simulations, and break-even calculations. Every model output is verified independently from raw results before entering the report, and the founder reviews the entire file personally before delivery.
confirmed
verified directly against primary records, official notices, or observed outcomes.
corroborated
supported by at least two independent, credible secondary sources.
reported
published in media or market commentary but not independently confirmed; labeled clearly as a reported claim.
unverified
single-source or unsubstantiated claim; excluded from analytical conclusions but logged in the record for completeness.
The source record — an excerpt from an internal reference dossier
| Claim | Source | Date | Stamp | Status |
|---|---|---|---|---|
| War-risk cover for the Persian Gulf suspended by five insurance clubs | Club notices, trade press | 2026-03 | confirmed | current |
| The strait was open to transit | Shipping wires | 2026-07-07 | corroborated | superseded 2026-08 — closed |
| A very large crude carrier earned ≈ $12M for one voyage | Broker reports | 2026-03 | corroborated | current |
| Northern route transit “down from 40 days to 20” | Market commentary | 2026-09 | reported | replaced by verified figure: 20–22 d |
| Change of ownership at the subject company | Single media report | — | unverified | excluded from findings |
WHAT OUR MODELS PROVIDE
Quantitative figures in our reports come from explicit, auditable mathematical models with documented assumptions. Whenever a calculation drives a conclusion, we show the methodology clearly so your internal team can inspect, challenge, or reproduce it.
WHAT THEY DO NOT PROVIDE
Guaranteed forecasts or professional advice. Forward-looking scenarios and risk estimates are analytical projections, not certainties. They are provided for informational and strategic planning purposes only and do not constitute financial, investment, legal, or insurance advice.
§ 03 — Services · engagements and rates
Four standard engagements, scoped and priced upfront.
Most client requirements fit one of the four formats below. Each is a fixed-scope, fixed-fee project with an agreed delivery timeline before work begins. For organizations with in-house analytics teams, we also build, document, and hand over custom mathematical models.
| Ref | Engagement | What you receive | Timeline | From |
|---|---|---|---|---|
| T1 | Single-company dossier | Public-record assessment of corporate structure, financial disclosures, open-source sanctions/litigation flags, and operational risk for one entity, built on 20+ cited sources with a complete source ledger | 2–3 weeks | $8,000 |
| T2 | Corridor or route dossier | Analysis of key actors, multi-dimensional risk factors, scenario definitions with early-warning indicators, and break-even cost models comparing your routing or sourcing options | 4–8 weeks | $25,000 |
| T3 | Monitoring and refresh | Ongoing open-source tracking of your specified entities or corridors, a quarterly update of the dossier, and interim alerts when material indicators shift | ongoing | $5,000 / quarter |
| T4 | White-label research | Any of the above produced to your firm’s template and formatting standards — built for consultancies, advisory practices, and law firms needing external research and modeling capacity | by agreement | $15,000 |
ENGAGEMENTS BEGIN AT $8,000. We focus on in-depth research and quantitative modeling rather than automated database pulls or quick background checks.
COMPLIANCE & ADVISORY NOTICE. All research is conducted strictly through lawful, publicly available open sources (OSINT). Dossiers and exposure screens are informational research inputs and do not constitute formal legal counsel, regulatory KYC/AML compliance certification, or legal sanctions-clearance opinions.
Custom models we build for your team — documented, handed over, yours to run
01
Corridor and route models
for logistics, shipping, and insurance teamsA quantitative comparison of your trade lanes across transit time, surcharges, and insurance costs that your staff can re-run as market conditions shift. Delivered with full documentation so every input and weight can be audited.
02
Disruption-recovery planning
for energy corporates and tradersAn optimization model tailored to your capacity, inventory, and contract obligations that calculates the financial impact of supply disruptions and helps evaluate contingency options.
03
Open-source exposure tracking
for risk desks and compliance teamsA structured monitoring workflow covering relevant public registries, trade press, and regional news, maintaining an auditable log of reported events, source dates, and confidence tags.
04
Methodology workshops
for in-house analysts and strategy teamsPractical training sessions for your analysts covering how optimization and simulation models are formulated, their analytical limitations, and how to verify AI-assisted research against primary sources.
§ 04 — A worked example · corridor risk, in numbers
Move the slider. See how the route math shifts.
This interactive model demonstrates how a corridor dossier translates geopolitical tension into an explicit cost comparison. Drag the tension slider to see how transit times, war-risk premiums, and surcharges affect three routes between the Persian Gulf and Northern Europe.
Model readout
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ILLUSTRATIVE DEMONSTRATION ONLY. While anchor points reflect reported 2026 market figures (peak war-risk premiums of 7.5–10% of hull value, container surcharges near $1,500/box, and Arctic transit times of 20–22 days), the interpolation curves and index weights are simplified for demonstration. This tool does not constitute maritime routing orders, voyage chartering advice, or insurance brokerage counsel.
§ 05 — Foundations · the disciplines behind the numbers
Established quantitative methods, applied to business risk.
Our quantitative assessments rely on four core disciplines that the founder has researched, published in, and taught at the university level—combined with practical industry experience building enterprise planning software.
Mathematical optimization models find the best operational plan under real-world constraints—helping teams evaluate sourcing, routing, disruption recovery, and portfolio allocation trade-offs.
- Published“Models for production planning under power interruptions” — Naval Research Logistics, 2013. Peer-reviewed research on industrial planning under supply disruptions.
- Benchmark scaleAn internal disruption-recovery benchmark model with 114,598 decision variables and 38,828 constraints, solved to proven optimality in ~2 minutes and independently verified.
- Academic foundationA decade teaching optimization, simulation, and statistics across three universities, following doctoral training in Industrial & Systems Engineering at Lehigh University.
The financial value of contingency planning can be modeled explicitly. In our benchmark energy-sector study, advance preparation reduced simulated disruption losses by $29.9 billion across the modeled horizon.
Simulation models allow you to stress-test operational plans against variable timelines, bottlenecks, and cost spikes before committing capital.
- Industry experienceRe-architected an enterprise omnichannel inventory and fulfillment simulator to run 30× faster, enabling large-scale strategic scenario testing.
- Benchmark studyDeveloped an eight-scenario disruption study for the energy sector modeling variable reopening timelines, repair rates, and commodity price regimes.
- Modeling approachVolatile factors—such as war-risk premiums or canal closures—are modeled across distinct regime states rather than treated as static averages.
Treating a volatile cost or transit time as a fixed average hides tail risk. Stress-testing requires modeling how systems behave when regimes shift.
Structuring large volumes of public reporting and trade data into consistent, comparable indicators—using statistical normalization so sudden bursts of media coverage don't distort the risk picture.
- System designBuilt an internal open-source screening pipeline that categorizes news and trade reporting semantically, linking every extracted claim directly to its source URL and date.
- CalibrationIndicator scoring is normalized against historical news volume so repetitive headlines on a busy news day do not artificially inflate risk scores.
- TransparencyWhere historical data is too sparse to backtest an early-warning indicator statistically, we state that limitation clearly in the report rather than overstating confidence.
Every quantitative score in our dossiers can be traced back to the underlying source documents and scoring weights.
We use large language models to accelerate multi-lingual reading, document indexing, and initial extraction across public sources—while keeping all mathematical modeling, source verification, and final conclusions under strict human control.
- ArchitectureA structured three-stage pipeline—collection, source-linked extraction, and human verification—where every intermediate output is auditable.
- VerificationMedia reports are treated as unverified claims until corroborated by primary filings, official notices, or multiple independent sources.
- Quality controlAI tools never generate mathematical figures or final conclusions unassisted; all calculations are executed in deterministic code and reviewed by the founder.
AI is effective at scanning thousands of pages quickly, but unreliable as a standalone analyst. We use AI to organize source material, and deterministic math and human review to reach conclusions.
§ 06 — Sample work · flagship reference dossier
What a finished dossier looks like.
Below is an excerpt from an internal reference dossier built to demonstrate our methodology on the Northern Sea Route. Hover — or tap — the highlighted blocks to reveal the specific analytical conclusions behind each finding.
FILE · ARCTIC-NSR-2026-09
PREPARED BY · CONSULTKITAPP LTD.
STATUS · COMPLETED 2026-09-15
INTERNAL REFERENCE DOSSIER · SAMPLE EXCERPT
F-01
When southern transit is suspended, the practical decision shifts from whether to reroute to which alternative corridor to commit to and when. The critical variable is whether the closure persists across your upcoming contract renewal window.
F-02
Verified transit times on the Northern Sea Route stand at 20–22 days, contrasting with the more optimistic savings figures circulating in unverified market commentary since July 2026.
F-03
The primary bottleneck on the northern corridor is physical capacity rather than shipper demand: icebreaker escort windows and ice-class vessel availability cap total volume — which directly affects commercial negotiating leverage on the route.
F-04
Regional war-risk premiums move in step-changes rather than gradual trends: the March 2026 P&I club suspensions represent a structural pricing shift in our scenario model.
8 SECTIONS21 CITED SOURCES6 RISK DIMENSIONS6 SCENARIOS, T0–T5BREAK-EVENS MODELEDEVERY CLAIM SOURCED & DATED
Benchmark study · disruption-recovery model for an energy supply network
An internal benchmark optimization model with 114,598 decision variables, solved to mathematical optimality and verified line by line. It demonstrates how we quantify the financial value of contingency planning under severe supply disruptions.
Modeled value with contingency plan$89,939M
Modeled value if disrupted unprepared$8,095M
Simulated value of preparedness (EVPI/VSS benchmark)$29,870M
Independent verificationline by line objective function recalculated directly from raw variable outputs
SAMPLE FILES AVAILABLE FOR REVIEW. Our full Northern Sea Route reference dossier, a banking-sector reference dossier, and two quantitative benchmark studies are available for walkthroughs during an initial consultation.
§ 07 — The practice
Direct principal execution, from scoping to delivery.
ConsultKitApp is a specialist, founder-led practice. You work directly with Dr. Çağrı Latifoğlu from the initial scoping call to final delivery—with no delegation to junior analysts and no outsourced research. We take on a limited number of engagements at a time so every file receives thorough verification.
Dr. Çağrı Latifoğlu
Founder — ConsultKitApp LTD.
An industrial engineer by training, holding a Ph.D. from Lehigh University, with a decade as a university faculty member and industry experience building optimization, simulation, and analytics systems in banking and retail technology. He founded ConsultKitApp to combine rigorous open-source research with verifiable mathematical modeling—giving decision-makers structured analysis they can audit and defend.
“Academic research teaches you how to formulate and prove a model. Industry teaches you how models behave when data is messy and stakes are real. This practice combines both disciplines.”
Education
- Ph.D., Industrial & Systems Engineering — Lehigh University, USA (2012); dissertation on production planning and power procurement portfolios
- M.Sc. and B.S., Industrial Engineering — Bilkent University, Türkiye
Prior positions
- Assistant Professor — TED University, Ankara (2016–2020)
- Assistant Professor & Interim Department Head — THK University, Ankara (2014–2016)
- Senior Data Scientist — Invent Analytics (2020–2022); re-architected an omnichannel strategic simulator, increasing execution speed 30×
- Senior Software Developer / Business Analyst — Yapı Kredi Bank (2013–2014)
Selected publications
- “Models for production planning under power interruptions” — Naval Research Logistics, 2013
- Ultra-compact photonic structure design — IEEE Journal of Lightwave Technology, 2018
- 2026 research papers: cardinality-constrained risk parity (ICAME’26); asset-price modeling with mean-reverting processes (YAEM 2026)
Company credentials
- KOSGEB Advanced Entrepreneur Grant — awarded at company launch
- Founder & General Manager, ConsultKitApp LTD. — 2024 to present, Ankara
§ 08 — Engage
Start with a scoping call, commit only to a clear brief.
01
Initial scoping conversation
We discuss the decision or exposure you are evaluating. If open-source intelligence and quantitative modeling can materially help, we explain how; if the question falls outside what public data or modeling can answer, we tell you upfront.
02
Written proposal within five business days
You receive a written scope of work specifying the fixed fee, research phases, anticipated data limitations, and delivery date before any commitment is made.
03
Transparent execution
You can review the source ledger and modeling assumptions as the work progresses, ensuring the final report directly addresses your operational questions.
Founding client slots
We are currently offering two discounted founding-client engagements this quarter under mutual NDA.
cagrilatifoglu@consultkit.app
+90 534 852 48 29
ConsultKitApp LTD. · Ankara, Türkiye — working worldwide