Kazakhstani anti-corruption NGO Adildik Joly uses Datanomix's Red Flags Management AI platform to flag risky public contracts, recovering KZT 244m in fines, 66 criminal cases and 1,100 administrative protocols since 2021, plus 170m tenge from an AI-detected VAT fraud scheme.
244 KZT million (~US$511,000)
Fines recovered (2021-2025)
66 cases
Criminal cases opened
1100 protocols
Administrative protocols issued
20 KZT billion (~US$42 million)
High-risk purchases flagged
170 million tenge (~US$400,000)
VAT-fraud recovery (2022 case)
22 US$ billion
Annual procurement spend screened
Details
Promoter
Adildik Joly (with Datanomix.pro)
Period
2021–2025
Keywords
anti-corruption, public procurement, civil society, open contracting
Context
Kazakhstan built a centralised e-procurement portal in 2015 that now generates over 100 million rows of contract records, and since 2021 the anti-corruption NGO Adildik Joly, which has 17 regional branches, has used this data to monitor public spending for fraud and waste.
Activities
Adildik Joly's tool, Red Flags Management, is built by the Kazakhstani company Datanomix, which grants civil-society groups free access as part of its social-responsibility policy; it uses large language models to extract structured data from unstructured procurement PDFs and screens transactions against 43 documented red-flag characteristics, such as single-bidder tenders or prices far above market rate, to generate automated fraud alerts.
Results
Since 2021 the effort has produced KZT 244 million in fines, 66 criminal cases and 1,100 administrative protocols against civil servants, alongside KZT 20 billion in high-risk purchases flagged, and a 2022 case using a bespoke VAT-fraud-detection algorithm recovered 170 million tenge for the state budget; Kazakhstan's State Audit Institutions separately report identifying US$305 million in financial violations using related tooling, with about 70% of flags caught before money changes hands.
Conclusions
These figures are self-reported by Adildik Joly and Datanomix rather than independently audited, and civil society's access to the underlying AI platform depends on a private vendor's voluntary grant that could be withdrawn, a real sustainability risk for a tool now central to Kazakhstan's anti-corruption monitoring.
Implementation
Indicative cost
Low (< €50k)
Time to results
Medium (1–3 years)
Staffing & skills
Adildik Joly (anti-corruption NGO, 17 regional branches), Datanomix.pro (private vendor providing the Red Flags Management platform)
Conditions for success
A centralised, machine-readable national e-procurement dataset (100 million+ rows) to screen
A private vendor voluntarily granting civil society free access to its AI platform as social responsibility
43 documented red-flag characteristics used to systematically screen transactions
Common failure modes
Civil society's access depends on a voluntary, revocable data-access grant from a single private company rather than a statutory mandate
The detection algorithm is proprietary and not independently auditable by the public
Where it fits
Governance type
civil-society/NGO
Scale
national
Income level
upper-middle-income
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