Professional AI Project Report Software — Sanction-ready DPR in 3 minutes.

Working capital assessment is the linchpin of any credit appraisal. Our platform computes the Maximum Permissible Bank Finance (MPBF) automatically, using the exact methodology each bank's credit department expects:

• →Tandon Committee's Second Method of Lending — applied by default, based on the proposed loan ticket size
• →Operating cycle — derived from real holding periods: raw materials, work-in-progress, finished goods, debtors, and sundry creditors
• →Margin Money — auto-computed at 25% of the working capital gap, validated against the benchmark Current Ratio of 1.33
• →Nayak Committee route — auto-invoked instead for MSME proposals below ₹5 crore, using the 20%-of-projected-turnover method
• →Every output aligns with RBI's Master Direction on Loans and Advances

Sound financial projections must withstand adverse scrutiny. Our software embeds a multi-variable Sensitivity Analysis module as a default deliverable — a non-negotiable requirement for term loans above ₹2 crore under most public sector bank credit policies:

• →Three stress variables — Sales Volume, Selling Price, and Raw Material Cost, shocked downward from 5% to 15%
• →Recomputed for every scenario — DSCR, Break-Even Point, and Cash Accruals
• →Sensitivity Matrix — demonstrates the project's resilience under stress
• →Auto-flagged risk — any scenario where DSCR slips below 1.25, or Project IRR converges with the Cost of Capital

This lets you advise the promoter on margin cushioning before submission — pre-empting the exact queries credit committees raise during sanction.

The software is trained and calibrated for every major MSME and entrepreneurship credit scheme in the Indian ecosystem — built into the engine and updated weekly, across 2,500+ business categories:

• →Schemes covered — PMEGP, Stand-Up India, PMFME, CGTMSE-backed proposals, PLI (Production Linked Incentive), and CLI (Capital Linked Incentive)
• →PMEGP — auto-reflects the 15–35% subsidy slabs based on category and location
• →CGTMSE — eligible proposals flagged for zero-collateral coverage up to ₹5 crore
• →Accounting treatment — follows Ind AS 20 on Government Grants, deducted from asset cost or recognised as deferred income, per lender preference

This removes the scheme-specific guesswork that typically delays sanction by weeks at the branch level.

The Means of Finance schedule is where most amateur reports collapse under bank scrutiny. Projectzo treats it as a structurally critical section, constructing a balanced funding pattern that satisfies every banking norm:

• →Funding sources — Promoter's Capital, Internal Accruals, Term Loan, Unsecured Loans from family, and (where applicable) Subordinated Debt or Quasi-Equity
• →Debt-Equity Ratio — enforced within the 2:1 to 3:1 band most public sector banks mandate
• →Promoter's Contribution — verified against the minimum 20–25% threshold required for greenfield projects
• →Source-and-Application Statement — capital infusion phased across implementation milestones, tied precisely to the Cost of Project

For NBFC and private bank proposals, gearing ratios are auto-adjusted to match each lender's published credit appetite — eliminating multiple iteration cycles.

Investment appraisal is incomplete without rigorous discounted cash flow analysis. Every project report includes a full institutional-standard appraisal suite as a standard output:

• →Standard metrics — Net Present Value (NPV), Internal Rate of Return (IRR), Modified IRR, Discounted Payback Period, and Profitability Index
• →WACC — derived dynamically from the project's debt-equity composition, prevailing term loan rate, and an industry-adjusted Cost of Equity (CAPM-equivalent)
• →Two return metrics — Project IRR (pre-tax operating cash flows) and Equity IRR (factoring tax shields, principal repayments, terminal value)
• →For VC/PE proposals — analysis extends to J-Curve modelling and exit-multiple sensitivities

This elevates the deliverable beyond bank-financing utility into investment-grade documentation.

Generic templates collapse the moment a credit officer asks an industry-specific question. Our AI is trained on sector-level intelligence drawn from MoSPI statistics, RBI Sectoral Deployment data, and leading rating agency industry reports:

• →Sector-specific data — relevant NIC code, capacity utilisation benchmarks, input-output ratios, and typical working capital cycle for the selected line of business (dairy, textiles, pharma, EV components, and more)
• →Narrative depth — auto-incorporates demand-supply gap analysis and Porter's Five Forces commentary
• →Regulatory framework — applied automatically (FSSAI for food, BIS for engineering, CDSCO for pharma, FAME-II for EVs)
• →Service-sector projects — methodology shifts toward revenue-per-employee and asset turnover ratios

This sectoral precision is what separates a bankable project report from a templated one.

Confidentiality of client financial data is non-negotiable. The platform is built on enterprise-grade security, with full white-label functionality for practising professionals:

• →Infrastructure — hosted on ISO 27001-certified infrastructure with AES-256 encryption at rest and TLS 1.3 in transit
• →Data isolation — every CA's workspace is logically isolated; no client data is ever used for model training
• →Retention — reports auto-purged from active servers per the retention period selected by the firm
• →White-label — reports generated with the firm's Logo, ICAI membership number, UDIN reference field, digital signature placeholder, and customised disclaimers
• →Access control — role-based permissions for articled assistants and partners

This positions the deliverable as the firm's own intellectual product — integrating seamlessly into a structured practice without compromising professional ethics or client privilege.