--- title: AI layers are landing on legacy data instead of replacing it description: Oracle, Databricks and Writer show the same pitch: keep the system you run, and add governed AI intelligence on top of it. canonical: https://hangingcontext.com/stories/2026-10-27/ai-layer-on-legacy-data/ last-updated: 2026-10-27 url: https://hangingcontext.com/stories/2026-10-27/ai-layer-on-legacy-data/ published: 2026-10-27T12:33:00Z edition: 2026-10-27T12 newsroom: artificial-intelligence beat: infrastructure trust: confirmed source_count: 4 cited_manifest_ids: ['1793100594308251455', '1793077313088412875', '1793024889149137424', '1793100594307056695'] --- # AI layers are landing on legacy data instead of replacing it *Oracle, Databricks and Writer show the same pitch: keep the system you run, and add governed AI intelligence on top of it.* Confirmed · 4 sources · Artificial Intelligence · Published 2026-10-27 12:33 UTC ## Key facts - Oracle says its E-Business Suite Intelligence provides prebuilt analytics and AI-assisted experiences for E-Business Suite customers, combining packaged E-Business Suite data, business semantics, analytics and AI-assisted experiences to reduce manual pipeline and modeling work. (self-reported) [cites: 1793100594308251455] - Oracle says the solution supports Finance, Procurement and Projects business areas, and that users can continue running E-Business Suite while using it. (self-reported) [cites: 1793100594308251455] - Databricks says Lakeflow Connect provides fully managed native connectors across SaaS applications, databases and file sources, storing ingested data as governed, managed tables in Unity Catalog, with connectors for Confluence, Notion, Glean, SharePoint and Google Drive. (self-reported) [cites: 1793077313088412875] - Writer says standard Snowflake tables showed 45 percent failure rates for insertions in its LLM tracing pipeline due to lock contention, and that after switching to Hybrid Tables, P50 insertion latency dropped from 2,362 milliseconds to 154 milliseconds and write failures dropped to near zero. (self-reported) [cites: 1793024889149137424] - Oracle says EPM Integration in Fusion Data Intelligence is designed to reduce data preparation work for finance teams, providing a managed path for EPM data and dimensions into Fusion Data Intelligence and supporting plan-versus-actual analysis and AI-enabled experiences. (self-reported) [cites: 1793100594307056695] ## Keep the ERP, add the intelligence Oracle says it has launched E-Business Suite Intelligence to provide prebuilt analytics and AI-assisted experiences for E-Business Suite customers, combining packaged E-Business Suite data, business semantics, analytics and AI-assisted experiences. The company says the solution aims to reduce the manual effort of building data pipelines and modeling application data by providing packaged business semantics out of the box. [cites: 1793100594308251455] The solution supports Finance, Procurement and Projects business areas, Oracle says, with finance intelligence helping teams understand financial performance and working capital, procurement intelligence helping teams improve visibility into spend and supplier performance, and projects intelligence helping teams improve visibility into cost, billing and funding. Users can continue running E-Business Suite while using the solution, the company says, and for customers using Intelligence, the solution can bring E-Business Suite and Fusion Applications insights together. [cites: 1793100594308251455] ## Finance data, joined without rebuilding it Oracle has also introduced EPM Integration in Fusion Data Intelligence, which the company says is designed to reduce data preparation work for finance teams. It provides a managed path for bringing data and dimensions from supported Oracle Fusion Cloud EPM applications into Fusion Data Intelligence, supports recurring scheduling and incremental data options, and supports plan-versus-actual analysis and AI-enabled experiences. [cites: 1793100594307056695] > **From Synorb** — Save what you follow as a Beacon. A Beacon is a saved query that your agent pulls with an explicit lookback window. Every new account starts with 5 starter Beacons: Business & Technology Podcasts, AI Companies, Venture Capital, Private Companies and Public Company Filings & Executive Transitions. [See Beacons](https://synorb.com/connect/start) Oracle says Fusion Cloud ERP actual financial activity is available for analysis in Fusion Data Intelligence, that customers define the semantic model and analytics that fit their requirements in EPM Integration, and that finance teams can move from high-level variance toward supporting detail using the integration. This suggests the value here is not a new ledger, but a shorter path from a variance a finance team already sees to the detail behind it. [cites: 1793100594307056695] ## Productivity data, governed for agents Databricks says it has expanded Lakeflow Connect to include native ingestion connectors for productivity tools, providing fully managed native connectors across SaaS applications, databases and file sources. Data ingested via Lakeflow Connect is stored as governed, managed tables in Unity Catalog, the company says, with connectors for Jira, Monday.com, Smartsheet, Aha! and GitHub, and for Confluence, Notion, Glean, SharePoint and Google Drive. [cites: 1793077313088412875] SharePoint and Google Drive connectors land unstructured files as rows with raw bytes in a content column, Databricks says, and Databricks uses ai_parse_document to turn raw bytes from document files into text for indexing. The company cites Toyota Finance Australia using Lakeflow Connect to ingest Jira data into Databricks, and VaxCare using the Confluence connector to feed its internal knowledge base into Databricks for AI agent grounding. [cites: 1793077313088412875] Databricks says Orizon synchronized over one million Jira tickets from 168 projects into Databricks, that the OpenAI connector allows attribution of AI spend by team and tracking of adoption, and that Lakeflow Connect includes connectors for OpenAI and Anthropic to govern AI usage. The pattern is consistent with the Oracle launches: the AI layer is useful only if the scattered data underneath it arrives governed, searchable and attributable, without a custom pipeline for each source. [cites: 1793077313088412875] ## The same logic inside an AI builder Writer, an enterprise AI platform, shows the same trade-off from the builder side. The company says its LLM tracing pipeline generates up to 600 rows per minute at peak, its primary traces table receives roughly 1.3 million rows per day, and it routes every customer request through LLM inference providers. Standard Snowflake tables experienced 45 percent failure rates for insertions due to lock contention, the company says, with P50 insertion latency on standard tables reaching 2,362 milliseconds. [cites: 1793024889149137424] After switching to Snowflake Hybrid Tables, Writer says P50 insertion latency dropped from 2,362 milliseconds to 154 milliseconds, write failures dropped from 45 percent to near zero, and it downsized the warehouse powering its ingest pipeline from medium to extra small. Hybrid Tables use row-oriented storage with row-level locking, the company says, and Writer uses a Snowflake Task to incrementally copy rows from the hybrid table to a standard table, using Hybrid Tables for high-velocity ingestion and standard tables for downstream analytics. [cites: 1793024889149137424] Writer says it evaluated writing tracing data to Postgres as an alternative to Snowflake, and is considering using Hybrid Tables for high-volume API logging data. The implication for tech executives is practical: when AI workloads stress an existing data estate, the fix may be a different table type or a governed connector on the estate already in place, rather than a migration or a new external store. [cites: 1793024889149137424] ## What is still unresolved - Whether packaged business semantics in E-Business Suite Intelligence cover a given customer finance, procurement or projects processes is not stated in the cited manifests. - Which EPM applications are supported by EPM Integration in Fusion Data Intelligence is described only as supported applications, without a list in the cited manifest. - How Lakeflow Connect pricing, throughput or connector limits apply to a given estate is not stated in the cited manifest. - Whether Writer results generalize to other tracing or logging workloads is not shown in the cited manifest, which reports one company pipeline. ## Decision card - **Useful for:** Tech executives deciding whether to add AI to existing ERP and productivity estates; Leaders weighing packaged business semantics against custom pipeline work - **Not for:** Teams that need a new system of record rather than intelligence on the existing one; Organizations whose data is not yet governed well enough to feed AI tools - **Compare against:** Custom data pipelines and modeling built in-house for each application; Migrating off a legacy ERP or productivity system to get modern analytics ## Provenance ledger | Manifest id | Title | Source | Claims used | Published | |---|---|---|---|---| | `1793100594308251455` | Put Your Oracle E-Business Suite Data to Work with AI-Assisted Intelligence | [oracle-blog](https://blogs.oracle.com/analytics/put-your-oracle-e-business-suite-data-to-work-with-ai-assisted-intelligence) | 1793101184030212887, 1793101184034784271, 1793101184032031146, 1793101184035769027, 1793101184043143164, 1793101184037237082, 1793101184038840695, 1793101184040626173 | 10-27 00:00 | | `1793077313088412875` | Unify your productivity and AI data with Lakeflow Connect | [databricks-blog](https://databricks.com/blog/unify-your-productivity-and-ai-data-lakeflow-connect) | 1793077602075897422, 1793077602078716842, 1793077602081927475, 1793077602080984795, 1793077602087566996, 1793077602089902859, 1793077602084441947, 1793077602086453891, 1793077602093038325, 1793077602091225635, 1793077602083795961 | 10-26 00:00 | | `1793024889149137424` | How Writer Keeps Its AI Infrastructure Running with Snowflake Hybrid Tables | [snowflake-medium-rss](https://medium.com/snowflake/how-writer-keeps-its-ai-infrastructure-running-with-snowflake-hybrid-tables-80f55dd652fa) | 1793025386170872781, 1793025386176753767, 1793025386177090331, 1793025386160818051, 1793025386158896097, 1793025386171045243, 1793025386179300992, 1793025386180967866, 1793025386174824364, 1793025386173712151, 1793025386182950453 | 10-26 00:00 | | `1793100594307056695` | A clearer, deeper view into financial performance | [oracle-blog](https://blogs.oracle.com/analytics/a-clearer-deeper-view-into-financial-performance) | 1793101182292401491, 1793101182294413955, 1793101182301837040, 1793101182297266857, 1793101182288246955, 1793101182299734002, 1793101182303415623 | 10-27 00:00 | ## Run these Manifests yourself Every Manifest cited here can be read in full with your own Synorb Key. Check the claims before you rely on them. 1. **Get a Synorb Key.** Click Generate Free Agent Key at https://synorb.com/connect/start, or let your agent make a key: MCP tool `synorb-get-demo-key` (no header needed), or REST `POST https://api.synorb.com/api/connect/demo-key` with a JSON body such as `{"client":"your-agent-name"}`. The key is the `api_key` field of the answer. Save the key. The 72 Hour Agent Demo key needs no email. It lasts 72 hours and can pull up to 25 Manifests. It includes 5 Beacons; all of them are starter Beacons. 2. **Read each cited Manifest by id.** REST: `GET https://api.synorb.com/manifests/by-id/{manifest_id}` with the header `Authorization: Bearer `. Ids are strings; do not parse them as numbers. The reply holds the source, the Signal (claims) and the Brief. 3. **Check the claim.** Match each sentence in the story to the claims in the Manifest it cites. The claim ids in the ledger point to them. Cited Manifest ids: - `1793100594308251455` - `1793077313088412875` - `1793024889149137424` - `1793100594307056695` ```sh for id in 1793100594308251455 1793077313088412875 1793024889149137424 1793100594307056695; do curl -s -H "Authorization: Bearer $SYNORB_KEY" "https://api.synorb.com/manifests/by-id/$id" done ``` > **From Synorb** — Claims with a source link. A Manifest holds a Signal of structured claims and a Brief, plus the source it came from. Your agent can check a sentence against it. 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