Why Organisations Choose Cognara.
DECISION INTELLIGENCE
Independent. Rigorous. Machine learning powered.
Built for the decisions that matter.
OUR DIFFERENCE
Seven Reasons Organisations Choose Cognara.
1.
Machine Learning Powered Intelligence
The infrastructure risk landscape is not static. Power prices shift between regimes. Curtailment patterns evolve. Regulatory environments change. A model calibrated on historical averages does not reflect where the market actually is today.
Our platform uses machine learning to continuously analyse market conditions, detect the prevailing regime and calibrate our simulation parameters accordingly. This means every analysis we produce reflects current market reality. Not a long run average. Not a historical assumption. The actual conditions your asset faces today and the realistic range of conditions it could face over its life.
The result is risk analysis that is more accurate, more relevant, and more credible than anything a static model can produce.
2.
Independence
When a developer produces their own risk analysis, they have an incentive to make the base case look as attractive as possible. When a lender produces their own credit analysis, they have an incentive to be conservative in ways that serve their interests. When a Big 4 firm produces advisory work, they have relationships with the parties in the deal that create subtle conflicts.
We have none of those incentives and none of those conflicts. We are an independent analytical voice with no stake in the outcome of your decision. No developer relationship. No lender relationship. No advisory mandate that creates pressure to reach a particular conclusion.
Our only incentive is to give you the clearest, most accurate picture of your risk exposure that our analytical capability can produce. That independence is not just a positioning statement — it is the foundation of the credibility of everything we deliver.
3.
Rigour Without Compromise
Institutional risk analysis is only as good as the standards it is held to. We hold our work to the standards of the most demanding counterparties our clients face - investment committees at global infrastructure funds, credit committees at institutional lenders, and LP reporting requirements of development finance institutions.
Every assumption we make is documented and disclosed. Every output is traceable back to its inputs. Every limitation is acknowledged honestly and explicitly. We do not produce analysis where the conclusions cannot be justified, where the methodology cannot be explained, or where the outputs cannot be defended under scrutiny.
If we cannot stand behind it in front of your most demanding counterparty, we do not deliver it.
4.
Calibrated to Your Context
There is a fundamental difference between a global model adapted to country specific conditions and a model built for country specific conditions from the ground up. The difference shows up in the calibration - in whether the power price dynamics reflect how IEX actually behaves, whether the regulatory risk parameters reflect how Indian state electricity commissions actually revise tariffs, whether the curtailment assumptions reflect how grid operators actually manage renewable dispatch.
Our infrastructure analytics are calibrated on real Indian and UK market data sourced directly from Indian and UK regulatory bodies and market operators. Not adapted from global benchmarks. Not estimated from generic emerging market parameters. Built specifically for the market our clients operate in.
Our genetic data analysis reflects the actual regulatory landscape and liability context our clients face - whether they are operating under Indian and UK data protection frameworks, GDPR, or both. We do not apply one-size-fits-all frameworks to contexts that require specific understanding.
5.
Accessible Institutional Quality
For most of the history of infrastructure project finance, the quality of risk analysis available to an organisation has been determined by its budget. Large global funds and major lenders could build in-house quantitative teams. Large transactions could justify Big 4 advisory engagements at Tens of lakhs per project. Everyone else made do with Excel models and deterministic sensitivity cases.
We believe that is the wrong way to allocate analytical rigour. The mid-market infrastructure developer raising debt needs credible probabilistic risk analysis as much as the global fund closing a billion dollar acquisition. The boutique transaction advisor preparing a client for a lender presentation needs institutional quality outputs as much as the Big 4 firm with a full quantitative team behind them.
We make machine learning powered, institutional quality risk analytics accessible to a wider range of organisations - at a fraction of Big 4 pricing, with faster turnaround, and without requiring an in-house quantitative capability.
6.
Transparency at Every Step
Risk analytics built on black box models is not risk analytics - it is a number with an authoritative label attached to it. The value of our work comes not just from the outputs we produce but from our clients' ability to understand, interrogate, and defend those outputs in front of the counterparties that matter.
We show our working at every step. We explain the assumptions that drive our outputs. We tell our clients where the analysis is strong and where uncertainty is greater. We acknowledge the limitations of our models honestly - not in a footnote but as a central part of how we communicate our results.
Our clients never receive outputs they cannot explain. They receive analysis they can defend in front of an investment committee, a credit committee, a board, or a regulator - because they understand what it says and why.
7.
Absolute Confidentiality
The data our clients share with us is among the most commercially sensitive information they hold. Asset parameters, financial structures, internal analysis, governance documents - these are not materials to be shared carelessly. We treat client information with the highest level of confidentiality as a matter of principle and practice. We sign a non-disclosure agreement before any data is shared. Client information is used solely for the commissioned analysis - it is never shared with third parties. Your data never leaves the engagement. What you share with us stays with us. Your analytical work and your commercial information.
Doing Nothing
Continuing with deterministic spreadsheets and three scenario sensitivity cases. The cost of doing nothing is invisible until it is not — when a deal underperforms, a covenant is breached, or a lender asks a question your model cannot answer.
What Are Your Other Options?
THE ALTERNATIVE
Building Internally
Developing machine learning powered probabilistic risk analytics in-house requires a dedicated quantitative team, months of development, and ongoing maintenance. This is not feasible for most mid-market infrastructure organisations and cannot justify building it for occasional use.
Going to Big 4
The Big 4 produce comparable analytical work at ₹20-50 lakh per engagement, on long timelines, with limited ability to iterate or update. We deliver the same rigour at a fraction of the cost, faster, and with a reusable engine that improves with each engagement.
We Hold Ourselves to the Same Standard We Apply to Our Work.
OUR COMMITMENT
Trust is not something we claim. It is something we earn - through rigour, transparency, and honest acknowledgement of what our analysis can and cannot tell you.
We Document Everything
Institutional risk analysis is only as good as the standards it is held to. Every assumption we make is documented and disclosed. Every output is traceable back to its inputs. We do not produce analysis where the conclusions cannot be justified, where the methodology cannot be explained, or where the outputs cannot be defended under scrutiny.
We Acknowledge Limitations
Risk analytics built on black box models is not risk analytics. We show our working at every step. We tell our clients where the analysis is strong and where uncertainty is greater. We acknowledge the limitations of our models honestly - not in a footnote but as a central part of how we communicate our results.
We Validate Before We Deliver
Our infrastructure analytics are calibrated on real market data sourced directly from regulatory bodies and market operators. We do not apply one-size-fits-all frameworks to contexts that require specific understanding. If we cannot stand behind it in front of your most demanding counterparty, we do not deliver it.
We Protect What You Share
We treat client information with absolute confidentiality. Client information is used solely for the commissioned analysis - it is never shared with third parties.