{ "note": "Watches applied to new approaches to market, aimed at graph, analytics, intelligence and AI work — the ground Neo4j, Palantir and Quantexa compete on. A watch fires only for notices first seen after it existed, so adding one here does not replay the archive; run `python atm.py --rematch` to replay it deliberately. Every condition a watch states must hold, and a watch that states nothing matches nothing. Terms match on word boundaries with an optional trailing 's', so 'participant' catches 'participants' but 'ndia' does not fire inside 'Indian'.", "fields": { "name": "label shown on the alert", "any": "fires if ANY of these terms appears", "all": "every one of these terms must appear", "none": "suppresses the match if any of these appears", "agency": "agency name substring", "panel": "Yes or No — panel arrangement", "multi_agency": "Yes or No — open to multiple agencies", "multi_stage": "Yes or No" }, "rejected_terms": { "note": "Measured against 306,542 real contract records before being left out. Do not re-add without re-testing.", "intelligence": "2,459 hits, nearly all the ACIC and ONI agency names", "criminal intelligence": "1,568 hits, all 'Australian Criminal Intelligence Commission' as the buyer", "kg": "kilograms, and the German 'GmbH & Co KG' company suffix", "ml": "millilitres, and suppliers named ML-Tech and ML Consultancy", "cypher": "'cypher locks repair' — physical door hardware", "embedding": "'embedding knowledge in policy', 'embedding links in websites'", "foundry": "trading names and bronze commemorative plaques", "targeting": "Defence targeting studies and 'health initiative targeting young people'", "profiling": "seabed sub-bottom profiling surveys", "rag": "red/amber/green status reporting", "mcp": "too many unrelated expansions; 'model context protocol' is watched instead", "graphql": "an API query language, unrelated to graph data", "licence renewal / subscription renewal": "436 and 238 hits — generic software and LexisNexis renewals", "software licences / licenses": "708 and 358 hits — every software purchase in the archive" }, "watches": [ { "name": "Graph and knowledge graph", "any": [ "neo4j", "graph database", "graph analytics", "graph data science", "graph platform", "graph technology", "graph model", "graph query", "knowledge graph", "property graph", "labelled property graph", "graph neural network", "graph machine learning", "graph algorithm", "graph visualisation", "graph visualization", "graph traversal", "graphrag", "graph rag", "connected data", "relationship data", "ontology", "taxonomy management", "semantic web", "semantic layer", "semantic model", "linked data", "triple store", "triplestore", "rdf", "sparql", "owl ontology", "digital thread", "tigergraph", "arangodb", "janusgraph", "amazon neptune", "cosmos db graph", "stardog", "ontotext", "graphdb" ] }, { "name": "Entity resolution and data matching", "any": [ "entity resolution", "identity resolution", "entity matching", "record linkage", "data matching", "data linkage", "probabilistic matching", "fuzzy matching", "name matching", "address matching", "deduplication", "de-duplication", "golden record", "master data management", "single view of customer", "single customer view", "customer 360", "client 360", "single source of truth", "entity extraction", "entity disambiguation", "beneficial ownership", "ultimate beneficial owner", "corporate structure", "relationship discovery", "relationship analysis" ] }, { "name": "Intelligence and investigative analytics", "any": [ "palantir", "quantexa", "graphaware", "ibm i2", "analyst's notebook", "analysts notebook", "palantir foundry", "gotham", "chainalysis", "link analysis", "network analysis", "social network analysis", "network analytics", "network intelligence", "investigative analytics", "investigation platform", "case management system", "intelligence platform", "intelligence analytics", "intelligence system", "all-source intelligence", "osint", "open source intelligence", "financial intelligence", "threat intelligence", "insider threat", "counter-terrorism", "counter terrorism", "border intelligence", "law enforcement analytics", "covert", "surveillance analytics", "lawful interception", "decision intelligence", "situational awareness" ] }, { "name": "Fraud, financial crime and integrity", "any": [ "fraud detection", "fraud analytics", "fraud analysis", "counter fraud", "counter-fraud", "anti-fraud", "fraud control", "fraud risk", "fraud prevention", "fraud investigation", "fraud ring", "fraud rules", "integrity analytics", "program integrity", "payment integrity", "improper payment", "incorrect payment", "overpayment", "leakage", "anti-money laundering", "aml", "money laundering", "counter-terrorism financing", "financial crime", "sanctions screening", "watchlist screening", "politically exposed person", "transaction monitoring", "know your customer", "kyc", "customer due diligence", "anomaly detection", "outlier detection", "risk scoring", "risk profiling", "risk analytics", "risk engine", "compliance analytics", "tax gap", "revenue protection", "revenue assurance", "debt analytics", "identity fraud", "identity crime", "collusion", "procurement fraud" ] }, { "name": "AI, LLM and retrieval", "any": [ "artificial intelligence", "ai", "machine learning", "deep learning", "generative ai", "genai", "gen ai", "gen-ai", "large language model", "llm", "foundation model", "small language model", "transformer model", "retrieval augmented generation", "retrieval-augmented generation", "vector database", "vector search", "vector index", "vector embedding", "text embedding", "semantic search", "similarity search", "natural language processing", "nlp", "natural language query", "text analytics", "text mining", "entity recognition", "ai agent", "agentic", "multi-agent", "ai assistant", "copilot", "chatbot", "conversational ai", "virtual assistant", "model context protocol", "prompt engineering", "fine-tuning", "responsible ai", "ai governance", "ai assurance", "ai safety", "ai ethics", "explainable ai", "model risk", "recommendation engine", "predictive analytics", "predictive model", "machine reasoning" ] }, { "name": "Data and analytics platforms", "note": "The broad net. Expect more volume than the others; mute this chip on the site if it drowns the rest.", "any": [ "data platform", "data fabric", "data mesh", "lakehouse", "data lake", "data warehouse", "data integration", "data pipeline", "data migration", "data modelling", "data modeling", "data architecture", "data strategy", "data governance", "data quality", "data stewardship", "master data", "metadata management", "data catalogue", "data catalog", "data lineage", "data discovery", "data observability", "reference data", "advanced analytics", "data analytics", "analytics platform", "analytics capability", "business intelligence", "data science", "data visualisation", "data visualization", "data warehouse modernisation", "databricks", "snowflake", "palantir", "sas institute", "tibco", "elasticsearch", "splunk", "mongodb", "informatica", "collibra" ] }, { "name": "Route to market — marketplaces and resellers", "any": [ "marketplace", "reseller", "aws marketplace", "azure marketplace", "value added reseller", "licence reseller", "license reseller", "software licensing agreement", "enterprise agreement", "buyict", "digital marketplace", "standing offer", "head agreement", "whole of government arrangement" ] }, { "name": "Panel arrangements open to every agency", "note": "No terms at all — this matches on the structural fields the OCDS API does not publish anywhere.", "panel": "Yes", "multi_agency": "Yes" }, { "name": "Multi-stage approaches", "note": "An EOI or shortlisting stage is the point at which a vendor can still get on the list.", "multi_stage": "Yes" }, { "name": "Disability and NDIS delivery", "note": "Kept from the earlier list: the NDIA is a live account question, and it approaches the market on AusTender even though it reports no contracts there.", "any": [ "ndis", "ndia", "national disability insurance", "ndis participant", "disability support", "assistive technology", "supported independent living" ] } ] }