Will AI Solve India's Food Inflation?
Evaluating the 2026 AI Mission
The government promised ₹10,372 Cr, 10,000+ GPUs, and an AI Centre of Excellence in Agriculture. But can algorithms actually fix what decades of cold-chain neglect and fragmented mandis could not? A data-driven audit.
⚡ Key Takeaways — Quick Read
- India's food inflation hit 8.4% (Apr–Dec 2024), driven by vegetables, pulses, and a supply chain that loses up to 40% of produce before it reaches the consumer. [1]
- The IndiaAI Mission (Cabinet-approved March 2024) has a total corpus of ₹10,372 Cr, with the Agriculture CoE allocated ₹990 Cr from FY2023-24 to FY2027-28. [2]
- Kisan e-Mitra, the AI chatbot for farmers, has answered over 93 lakh queries in 11 languages — a proof-of-concept that AI can reach India's 140 million farm holdings. [3]
- The new Bharat-VISTAAR tool announced in Union Budget 2026-27 integrates AgriStack portals with AI for customised farm advisory — a significant upgrade on existing digital agriculture tools. [3]
- A 10% AI-driven productivity gain across India's farm sector could generate an estimated ₹70,000 Cr in annual value for farmers — the single largest poverty-reduction opportunity of the decade, per Union Minister Dr. Jitendra Singh. [4]
- The critical gap: AI initiatives address advisory and prediction well, but cold-chain infrastructure, road connectivity, and mandi reform — the physical causes of 33% annual food losses — require parallel non-AI investment to see lasting results. [5]
1. The Problem AI Is Being Asked to Solve
Before evaluating whether artificial intelligence can fix India's food inflation, we need to be precise about what is actually broken. The word "inflation" on a grocery receipt is the end of a very long, very inefficient chain — one that starts at a farm in Nasik, runs through a network of commission agents, mandis, cold storages, and diesel trucks, and ends at your vegetable vendor's cart. The chain is where the money leaks.
As our pillar article on India's inflation macro reality documented, the Economic Survey 2024-25 reported food inflation surging to 8.4% between April and December 2024, primarily driven by vegetables and pulses. [1] This is not a new problem. India has been the world's second-largest producer of fruits and vegetables for decades — yet it simultaneously allows an estimated 40% of that produce to be lost before it ever reaches the consumer. [6]
India grew enough food. The problem is the system that moves it from farm to plate — a system riddled with information asymmetries, inadequate cold storage, too many intermediaries, and diesel-dependent logistics. Fixing supply chain wastage by even 10 percentage points could put meaningful downward pressure on retail food prices. That is the task AI has been assigned.
Where India's Food Gets Lost: The Waste Anatomy
| Supply Chain Stage | Average Loss (%) | Primary Cause | AI Fix Potential |
|---|---|---|---|
| Harvesting | 4–8% | Manual harvesting errors, improper tools | 🟡 Moderate — drone-assisted harvest timing |
| Transportation | 5–8.5% | No refrigeration, road quality, overloading | 🟡 Moderate — route optimisation, ETA prediction |
| Storage | 3.5–5.7% | Inadequate cold chain, poor infrastructure | 🟢 High — IoT + AI for temperature management |
| Retail Stage | 5–15% | Improper handling, overstocking, no demand signal | 🟢 High — demand forecasting, inventory AI |
| Total Annual Loss | ~33% | 74 million tonnes · ₹13B+ economic value | Target: reduce to 15–20% by 2030 |
Sources: ScienceDirect (2024), FAO India Profile, UNEP Food Waste Index Report 2024 [5][6]
The numbers are damning. India loses 74 million tonnes of food per year — equivalent to 22% of foodgrain output. [7] This is not a marginal inefficiency; it is a structural haemorrhage that directly inflates retail prices by creating artificial scarcity. When 40% of tomatoes rot before reaching the mandi, the 60% that does arrive commands a price premium that the aam aadmi cannot afford.
2. The IndiaAI Mission: Architecture and Ambition
The Cabinet approved the IndiaAI Mission on 7 March 2024 — a landmark policy decision that repositioned artificial intelligence from a buzzword in government speeches to a line item in the Union Budget. The mission's total corpus stands at ₹10,372 Cr, making it one of the largest government-backed AI programmes in the developing world. [2]
In the Budget 2025-26 & AI section of our pillar article, we documented that the IndiaAI Mission received ₹2,000 Cr in Budget 2025-26 — a staggering 1,056% increase from FY25, signalling a shift from pilot to scale. This sits alongside the AI Centre of Excellence in Agriculture (₹990 Cr, FY2023-27) and the new Digital Agriculture Mission (₹2,817 Cr). [8] Together, these represent India's most coordinated policy bet on technology as an inflation-cure.
| Initiative | Allocation | Period | Food Inflation Relevance |
|---|---|---|---|
| IndiaAI Mission (Total) | ₹10,372 Cr | 2024 onwards | Sovereign compute + datasets for all sectors including agriculture |
| IndiaAI Budget 2025-26 | ₹2,000 Cr (+1056% YoY) | FY2025-26 | Scale-up phase; AI-driven supply chain efficiency |
| AI CoE: Agriculture | ₹990 Cr | FY2023-2027 | Crop price monitoring, pest prediction, climate-resilient farming |
| Digital Agriculture Mission | ₹2,817 Cr | FY2021-27 | AgriStack, farmer identity, digital crop advisory |
| Bharat-VISTAAR (Budget 2026-27) | To be announced | FY2026-27 | Multilingual AI integrating AgriStack + ICAR practices |
| AI CoE: Education | ₹500 Cr | FY2025-26 | Skilled workforce → productivity → lower unit-cost inflation |
| GPU Infrastructure (10,000+ GPUs) | Part of ₹10,372 Cr | 2024-27 | Sovereign compute backbone enabling all sector AI models |
Sources: MeitY / PIB [2], Union Budget 2025-26 [9], indiaai.gov.in [3]
The mission's architecture is built on three foundations. First, sovereign compute capacity: over 10,000 GPUs through public-private partnerships to ensure India's AI development is not dependent on foreign cloud providers. Second, the IndiaAI Dataset Platform — a unified, high-quality repository of anonymised data accessible to startups and researchers, solving the data scarcity problem that has historically crippled Indian AI projects. Third, the Centres of Excellence — sector-specific hubs where academic research, government policy, and private innovation converge. [2]
3. The AI CoE in Agriculture: What It Is Actually Doing
The AI Centre of Excellence for Agriculture is not a research lab in a university basement. It was announced by Union Education Minister Dharmendra Pradhan as part of the "Make AI in India and Make AI Work for India" vision, with a mandate to empower farmers with AI-driven solutions that address real on-ground constraints: weather unpredictability, pest attacks, price volatility, and market access gaps. [10]
Current Deployments: What Is Already Working
The most tangible evidence of the CoE's progress is Kisan e-Mitra — a voice-enabled, AI-powered chatbot launched in 2023 that allows farmers to query government schemes in their own language. By December 2025, it had handled over 93 lakh queries across 11 regional languages, addressing questions on the PM Kisan Samman Nidhi, the Kisan Credit Card, and the Pradhan Mantri Fasal Bima Yojana. [3] As of early 2026, it processes over 8,000 farmer queries per day.
- Kisan e-Mitra: 93 lakh queries answered; 11 languages; 8,000+ daily queries — AI can reach India's most marginal farmers.
- Drone surveillance: Early-stage deployment for pest detection and crop health mapping across pilot districts in Maharashtra and Andhra Pradesh.
- Price forecasting models: Private agri-startups (backed by Omnivore, Blume Ventures) using ML to predict commodity price movements at the mandi level — helping farmers decide when to sell.
- Satellite-based crop monitoring: ISRO-integrated tools now allow real-time assessment of crop yield and distress signals across states, improving procurement planning.
- Bharat-VISTAAR (2026-27): Multilingual AI tool integrating AgriStack with ICAR agronomic practices — the most ambitious advisory platform India has attempted. [3]
India's agri-tech ecosystem has also grown substantially around these government programmes. As of 2023, the country hosts over 2,800 agri-startups, with ₹6,600 Cr in private equity funding raised over four years. [8] The AI Mission's ₹990 Cr in the Agriculture CoE acts as a catalyst and de-risking signal for this private capital.
At the AI4Agri 2026 Summit in Mumbai, Union Minister Dr. Jitendra Singh crystallised the government's ambition in a single number: "India's 140 million farm holdings, most of them small and marginal, could together generate an estimated ₹70,000 Cr in annual value if AI-enabled advisories help each farmer save even ₹5,000 a year through better input timing, pest prediction and market linkage." [4]
"The next agricultural revolution in India will not be about a new seed or a new pesticide. It will be about a farmer in Vidarbha knowing, on his phone, what his tomato will fetch at three different mandis tomorrow morning."
— Dr. Jitendra Singh, Union Minister of State (MoS) S&T, at AI4Agri Summit 2026India ranked 3rd globally in AI competitiveness in Stanford University's 2025 Global AI Vibrancy Tool, measured across AI growth and innovation between 2017 and 2024 — reflecting strengths in AI talent, research output, startup density, and governance frameworks. [11] This structural advantage in AI capability is what makes the Agriculture CoE's ambitions credible rather than aspirational.
I was at a kirana store in my neighbourhood in early April 2026, and the shopkeeper — a man who supplies roughly 300 households in the area — told me he'd started using an app on his phone that sends him projected tomato and onion prices for the coming two weeks, sourced from mandi transaction data. He was sceptical the first month. By the third month, he said it had cut his over-ordering losses by "roughly a third." He doesn't know it's AI. He calls it "the phone." That anecdote captures both the promise and the communication gap of India's AI-in-agriculture push: the tools are beginning to work, but the narrative hasn't reached the people using them. The bigger question — one that this article tries to answer — is whether these individual wins can aggregate into systemic food price relief at a national scale. The evidence is cautiously optimistic, but the timeline is longer than any budget cycle.
4. The Supply Chain Wastage Problem: Can AI Actually Fix It?
This is the central question — and it requires an honest answer rather than a promotional one. AI's potential in agricultural supply chains is real. But its limitations are equally real, and conflating the two does a disservice to both policymakers and the farmers whose livelihoods depend on getting this right.
4.1 — Where AI Can Genuinely Reduce Wastage
Demand forecasting is where AI has the clearest, most demonstrable impact. Retail chains and large distributors using machine learning to predict weekly demand for perishables can reduce overstock-driven spoilage significantly. Organisations deploying AI-based inventory management have reported 15–25% reductions in perishable waste in early Indian deployments, according to data aggregated by the Cornell TCI research group. [8]
Cold storage optimisation is another high-potential zone. IoT sensors combined with AI controllers can maintain optimal temperature and humidity across storage facilities — reducing the 3.5–5.7% storage-stage losses that currently compound across India's fragmented cold chain. The AI CoE's mandate explicitly includes this domain. [10]
Price signal transmission — perhaps AI's most economically significant agricultural application in India — addresses the information asymmetry that has plagued Indian farmers for generations. When a farmer in Vidarbha doesn't know that tomatoes are trading at ₹90/kg in Delhi while he's selling at ₹12/kg to a commission agent, the system is exploiting his ignorance. AI-powered price discovery platforms (the better implementations of e-NAM, and private apps like DeHaat and Ninjacart) are beginning to compress this spread, directly improving farmer income while potentially cooling volatility-driven retail price spikes. [8]
In December 2025, the IndiaAI Mission (under MeitY), in collaboration with the Government of Maharashtra's AI and Agritech Innovation Centre and supported by the World Bank, invited global submissions for a compendium documenting real-world AI solutions in agriculture — specifically seeking deployed, scalable tools that enhance crop planning, strengthen farm operations, expand market access, and improve financial resilience for farmers. The compendium's goal is cross-sector, cross-country learning. Its publication will be a landmark mapping of what actually works in field conditions. [12]
4.2 — Where AI Cannot Fix the Problem Alone
Here is the uncomfortable truth: the biggest driver of food wastage in India is not a lack of data — it is a lack of physical infrastructure. India has an estimated cold storage deficit of over 35 million metric tonnes. Roughly 30% of perishable goods go to waste specifically due to inadequate refrigeration during transportation and storage. [13] No AI model can keep tomatoes cool in a truck that has no refrigeration unit.
Similarly, the fragmentation of the mandi system — with its layers of commission agents, weigh-bridge operators, and licensed traders who extract margins at every step — is a governance and regulatory problem, not a data problem. The APMC (Agricultural Produce Market Committee) Acts in many states still prevent farmers from selling directly to end buyers. AI can provide price signals, but if the farmer is legally or structurally unable to act on those signals, the information is worthless.
- Build the 500,000 kilometres of rural roads needed to reduce transit time for perishables
- Construct the cold storage capacity India is missing — an infrastructure gap worth tens of thousands of crores
- Reform APMC laws to give farmers direct market access — a political economy challenge that has defeated reform efforts for 25+ years
- Provide the last-mile banking access that farmers need to receive digital payments for their produce
- Fix the diesel dependency of the entire agricultural logistics chain — a problem that the Hormuz crisis has made painfully visible
5. The Inflation Transmission: How AI Savings Reach Your Plate
Even if one accepts that AI can reduce supply chain wastage by a meaningful margin, the question remains: how quickly, and by how much, does that reduction translate into lower retail food prices? The transmission mechanism matters enormously for the inflation question.
| AI Intervention | Waste Reduction Potential | CPI Impact Estimate | Timeline to Price Relief | Confidence |
|---|---|---|---|---|
| Demand forecasting at retail/wholesale | 15–25% of retail-stage losses | 0.1–0.3% CPI reduction | 1–3 years | 🟢 High |
| Cold storage IoT optimisation | 10–20% of storage-stage losses | 0.05–0.15% CPI reduction | 3–5 years | 🟡 Medium |
| Price signal platforms (e-NAM + AI) | Reduces price volatility, not quantity loss | Volatility dampening; 0.2–0.5% peak-season reduction | 2–4 years | 🟡 Medium |
| Crop advisory + yield prediction | 5–10% yield improvement; better crop planning | 0.3–0.7% CPI reduction (long-term) | 5–10 years | 🟡 Medium |
| AI-driven logistics route optimisation | 5–8% reduction in transit losses | 0.05–0.1% CPI reduction | 2–4 years | 🟢 High |
| Cumulative potential (optimistic scenario) | 10–15 percentage point reduction in total food loss | 0.5–1.5% structural CPI reduction | 5–10 years | 🟡 Medium |
Estimates based on CPI basket weights (MoSPI), FAO loss data, and Cornell TCI research. These are structural projections, not annual forecasts. [5][8]
The honest read of this data is that AI-driven supply chain improvements could deliver a 0.5 to 1.5 percentage point structural reduction in food CPI over a 5–10 year horizon — not a quick fix, but a genuine and durable one. Given that India's food inflation has averaged above 6% for much of the past decade, even a 1 percentage point structural reduction would be enormously significant — not just for headline CPI, but for the tens of millions of Indian households whose nutrition choices are directly constrained by food prices.
For context: the pillar article notes that the RBI's 4% CPI mandate has been extended to March 2031. A structural 1% reduction from supply-side AI efficiency gains would meaningfully ease the RBI's task — requiring less monetary tightening (higher interest rates) to achieve the same inflation outcome. That is a macroeconomic dividend far larger than the direct consumer price impact.
6. The AI-Inflation Nexus: Macro and Microeconomic Angles
6.1 — AI and the WPI–CPI Transmission Gap
As our pillar article explained, WPI (Wholesale Price Index) surges typically reach the CPI basket within 3–6 months as manufacturers pass on costs. AI-driven supply chains have the potential to reduce the amplitude of this pass-through by buffering against sudden supply shocks. If AI systems can predict a tomato price spike in Maharashtra two weeks in advance — based on satellite crop assessment data — procurement managers can route supply from alternative regions before the mandi price explodes. This spatial arbitrage capability is perhaps AI's most underappreciated anti-inflation function.
6.2 — The Hormuz Compounding Problem
The 2026 Hormuz crisis has added an external amplifier to India's food inflation. Diesel prices — frozen at retail but unsustainable for OMCs — power the entire agricultural transport chain. AI-optimised logistics routes that reduce the number of truck kilometres per tonne of food delivered are, in this context, also an energy-efficiency play. Every kilometre saved is diesel not burned and cost not passed on. The Hormuz article noted that every $10/bbl oil price rise adds approximately $12 billion to India's import bill — AI supply chain efficiency is a partial structural buffer against this volatility.
6.3 — The Fiscal Dividend of Reduced Wastage
India's food subsidy bill under PMGKAY and the National Food Security Act runs to tens of thousands of crores annually. If AI-driven supply chain improvements reduce post-harvest losses by even 10 percentage points — converting currently wasted food into available supply — the effective procurement requirement drops, the minimum support price (MSP) pressure eases, and the fiscal deficit narrows. Less government spending on food subsidies means more fiscal headroom for infrastructure and education — a virtuous cycle that compounds over time.
7. Critical Evaluation: Is the AI Mission Enough?
The IndiaAI Mission is genuinely ambitious. Its ₹10,372 Cr corpus, its GPU infrastructure push, and the Agriculture CoE's ₹990 Cr allocation represent a serious, well-architected policy intervention. India ranks third globally in AI competitiveness. [11] The private sector has added 2,800 agri-startups. Kisan e-Mitra is answering 8,000 queries a day. The pieces are assembling.
But an honest evaluation must also ask: is this enough? Is the pace fast enough? Is the focus right?
📊 The CrunchyCashFlow Verdict: AI Mission vs. Food Inflation
- Sovereign compute strategy reduces AI dependency on foreign infrastructure
- Agriculture CoE addresses real structural problem with sustained funding over multiple years
- Kisan e-Mitra proves AI can scale to 140 million small farmers
- Private capital attracted — ₹6,600 Cr PE in agri-tech over 4 years
- Bharat-VISTAAR integration of AgriStack + ICAR is the right systemic move
- IndiaAI Dataset Platform solves the data access bottleneck for startups
- AI advisory without cold-chain infrastructure is advice farmers can't act on
- APMC reform absent — farmers still cannot fully access digital price signals
- ₹990 Cr for AgriCoE vs ₹13B+ in annual food losses: funding asymmetry is stark
- Timeline mismatch: AI delivers 5–10 year results; food inflation is a now problem
- Digital divide: smartphone and internet access still limits AI reach in the most food-insecure districts
- No dedicated AI-in-cold-chain programme yet — the highest-value intervention
Bottom Line: The AI Mission is necessary but not sufficient. India needs AI plus cold chain investment, APMC reform, road infrastructure, and farmer financial inclusion running in parallel. AI is the intelligence layer. But the physical layer — roads, storage, power — still needs to be built.
8. What This Means for Your Wallet — and What to Do Now
Understanding the 5–10 year horizon of AI-driven food inflation relief matters enormously for personal financial planning. If structural relief is a decade away, you cannot passively wait for the government's AI Mission to protect your purchasing power. You need to act at the portfolio level — today.
Food inflation at 8.4% in 2024 and a projected 5–6% CPI through Q3 2026 means that a savings account at 3% is delivering a guaranteed negative real return. Your money is shrinking in purchasing power even as the balance grows in nominal terms. This is precisely the "Silent Thief" described in our pillar article — and why the standard advice to "keep 6 months of expenses in a savings account" needs to be re-examined critically.
The AI Mission's food inflation fix is a 5–10 year structural play. Your savings account is losing purchasing power today. This companion article breaks down 5 specific asset classes — Gold ETFs, inflation-linked bonds, equity sectors, REITs, and more — that have historically outpaced Indian inflation, with data-backed analysis and allocation guidance for salaried investors.
Read the Full Asset Guide →9. What India Needs to Do Next: A Policy Checklist
The AI Mission has set the direction. What it needs is complementary action across three non-AI domains to make its agricultural ambitions real:
| Policy Action | Current Status | Food Inflation Impact | Urgency |
|---|---|---|---|
| Cold Chain National Mission — dedicated programme with ₹25,000+ Cr corpus | Fragmented; partial PM Gati Shakti coverage | Highest — addresses 30% perishable loss | 🔴 Immediate |
| APMC Reform 2.0 — uniform national model law for direct farmer-buyer transactions | Stalled after 2020 farm laws rollback | High — enables AI price signals to translate to farmer action | 🔴 Immediate |
| Rural Road Connectivity — PM Gram Sadak Yojana acceleration | 70% rural road connectivity; gaps in North-East, hilly areas | Medium — reduces transit losses and transport cost inflation | 🟠 Medium-term |
| AI in Cold Chain — dedicated sub-mission within AgriCoE for IoT+AI cold storage | Not yet a formal programme | High — highest ROI intervention for waste reduction | 🔴 Immediate |
| Farmer Financial Inclusion — Jan Dhan + Aadhaar seeding for digital payment in mandis | ~80% Jan Dhan coverage; last-mile gaps remain | Medium — enables AI platform adoption and direct payment | 🟠 Medium-term |
| Bharat-VISTAAR Scale-up — full national deployment with regional language support | Announced in Budget 2026-27; rollout pending | Medium — advisory only; complementary to infrastructure | 🟡 On Track |
CrunchyCashFlow policy analysis. Sources: PIB, MeitY, Economic Survey 2024-25 [1][9]
Frequently Asked Questions
Conclusion: The Algorithm Is Ready. The Infrastructure Is Not.
The question "Will AI solve India's food inflation?" deserves a precise answer rather than either breathless optimism or cynical dismissal.
Yes, AI will meaningfully contribute to reducing India's food inflation — over a 5–10 year horizon, through a combination of demand forecasting, price signal platforms, cold storage optimisation, and crop advisory tools. The ₹10,372 Cr IndiaAI Mission, the ₹990 Cr Agriculture CoE, Kisan e-Mitra's 93 lakh queries, and Bharat-VISTAAR's multilingual advisory integration represent a coherent, well-funded, and increasingly operational architecture. India's 3rd global ranking in AI competitiveness confirms it has the talent to execute. [11]
No, AI alone will not solve India's food inflation — because 40% of fruit and vegetable losses are caused by the absence of cold storage, the quality of rural roads, and APMC regulatory structures that no algorithm can fix. The intelligence layer is being built. The physical layer — where tomatoes actually rot, where trucks have no refrigeration, where farmers are legally barred from selling to the highest bidder — still requires sustained, large-scale infrastructure investment and regulatory reform that the AI Mission does not provide. [5][13]
As we noted in the Budget 2025-26 & AI section of our pillar article: technology is India's long-term structural inflation cure. But structural cures take time. In the meantime, the Silent Thief keeps nibbling. The only rational personal response is to stop keeping all your money where the thief can find it most easily — in savings accounts — and to invest in assets that outpace inflation. Stay Crunchy.
This cluster article is part of the CrunchyCashFlow Inflation Series, expanding on the Budget 2025-26 & AI section of our pillar:
📖 Pillar Article: Understanding Inflation in India — Part 1: The Macro Reality →
📑 References & Citations
- Press Information Bureau, Govt of India. Highlights of the Economic Survey 2024-25. February 2025. pib.gov.in
- Principal Scientific Adviser, Govt of India. AI Mission Initiatives — IndiaAI Mission Overview. psa.gov.in
- Press Information Bureau, Govt of India. Artificial Intelligence Transforming Indian Agriculture. February 14, 2026. pib.gov.in
- Press Information Bureau, Govt of India. India's Next Agricultural Revolution Will Be AI-Driven — Dr. Jitendra Singh at AI4Agri 2026 Summit. February 22, 2026. pib.gov.in
- ScienceDirect / Transportation Research Part E. Challenges and Opportunities for Agri-Fresh Food Supply Chain Management in India. 2024. sciencedirect.com
- Food and Agriculture Organization (FAO). India Country Profile — Food Loss and Waste. FAO Platform on Food Loss and Waste. fao.org
- UNEP / Khan Global Studies. Food Waste Index Report 2024 — India Loss Data. khanglobalstudies.com
- Cornell TCI (Shree Saha). Bringing Intelligence to the Fields: Opportunities and Equity in India's AI-Driven Agriculture. September 2025. tci.cornell.edu
- Ministry of Finance, Govt of India. Union Budget 2025-26. February 1, 2025. indiabudget.gov.in
- IndiaAI.gov.in. AI in Agriculture in 2025: Transforming Indian Farms for a Sustainable Future. indiaai.gov.in
- Stanford University. Global AI Vibrancy Tool — India AI Competitiveness Ranking 2025. aiindex.stanford.edu
- News on Air / MeitY. IndiaAI Mission Invites Global Submissions on AI Applications in Agriculture. December 17, 2025. newsonair.gov.in
- Solwearth / India Business Trade. Feeding a Billion: Identifying the Gaps in India's Food Supply Chain. July 2, 2025. indiabusinesstrade.in
- MoSPI. Consumer Price Index — Press Release, March 2026. mospi.gov.in
- Reserve Bank of India. Monetary Policy Report 2026. rbi.org.in
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