Meta tags:
description=Bridging the data Infrastructure gap for AI. Ensure AI data governance, make AI training and agent runs reproducible, reduce access friction.;

Headings (most frequently used words):

data, lakefs, the, and, for, ai, ready, with, how, access, is, your, governance, in, market, tools, control, infrastructure, quality, you, named, representative, vendor, 2025, gartner, guide, dataops, of, development, to, formats, built, on, our, architecture, compliance, ensure, make, agent, help, faster, more, learn, when, agents, touch, production, department, energy, ensures, proper, model, every, storage, stack, all, orchestration, plane, highly, scalable, version, manages, lifecycle, provenance, unified, engineering, teams, clock, ticking, enable, by, design, training, runs, reproducible, reduce, friction, curious, can, deliver, projects, efficiently, case, study, arm, powers, its, management, partners, about, anywhere, new, need, getting, started, proof, preventive, controls, isolated, audit, across, workload, action, go, improved, velocity, reduced, costs, stronger, adds, foundation, tech, connects, object, that, uses, s3, interface, supports, broadly, used, compute, engines, common, ingest, technologies, are, integrated, into, agnostic, regardless, format, re, using, will, support, it, manage, workflows, better, popular, supported, seamlessly, integrate, whatever, ml, includes, mandatory, lake, health, maintain, highest, together, pick, up, slack, table, file, unstructured,

Text of the page (most frequently used words):
data (71), lakefs (39), and (36), the (28), for (22), with (20), more (12), read (11), ready (11), #storage (10), how (9), our (8), control (8), #access (8), your (7), governance (7), tools (7), engineering (7), quality (7), open (7), agents (6), production (6), market (6), close (6), from (5), development (5), case (5), product (5), infrastructure (5), learn (5), aws (5), formats (5), community (4), about (4), docs (4), named (4), representative (4), vendor (4), 2025 (4), gartner (4), guide (4), dataops (4), new (4), try (4), orchestration (4), every (4), software (4), reduced (4), run (4), across (4), agent (4), version (4), compliance (4), book (4), demo (4), pricing (4), share (3), all (3), not (3), use (3), contact (3), newsroom (3), careers (3), blog (3), cloud (3), talk (3), engineer (3), model (3), study (3), that (3), distributed (3), lake (3), stack (3), manage (3), workflows (3), you (3), are (3), azure (3), used (3), compute (3), engines (3), object (3), models (3), time (3), different (3), what (3), result (3), projects (3), velocity (3), any (3), controls (3), teams (3), improved (3), faster (3), isolated (3), built (3), plane (3), company (3), resources (3), developers (3), solutions (3), join (2), experts (2), best (2), practices (2), slack (2), privacy (2), help (2), department (2), energy (2), ensures (2), proper (2), when (2), touch (2), summit (2), have (2), but (2), excited (2), has (2), together (2), deliver (2), trusted (2), architecture (2), studies (2), machine (2), learning (2), ensure (2), scale (2), red (2), hat (2), openshift (2), databricks (2), amazon (2), seamlessly (2), integrate (2), pipelines (2), iceberg (2), gcp (2), technologies (2), local (2), netapp (2), minio (2), dell (2), workflow (2), ingestion (2), streaming (2), team (2), launch (2), after (2), now (2), same (2), can (2), cases (2), running (2), experiment (2), analysis (2), science (2), branching (2), some (2), lockheed (2), martin (2), streamlined (2), mlops (2), test (2), isolation (2), before (2), stronger (2), costs (2), arm (2), full (2), management (2), users (2), reduce (2), end (2), training (2), action (2), make (2), preventive (2), audit (2), workload (2), yourself, knowledge, fellow, peers, discover, introduce, pick, copyright, rights, reserved, sell, personal, information, terms, settings, policy, need, getting, started, this, summary, presented, 2024, project, alexandria, digital, library, research, according, dun, bradstreet, momentum, survey, organizations, active, initiatives, only, say, their, adequately, been, thought, leadership, attimis, onebucket, seagate, exos, bring, global, prem, anywhere, explore, monte, carlo, griffin, great, expectations, deequ, bigeye, anomalo, mandatory, health, maintain, highest, vertex, snorkel, ray, python, pandas, mlflow, lancedb, labelbox, jupyter, hugging, face, datasets, hex, e2b, domino, labs, datarobot, dataloop, dataiku, dask, sagemaker, bedrock, agentcore, whatever, includes, seqera, prefect, nextflow, metaflow, lakeflow, declarative, kubeflow, dbt, dagster, argo, wfs, airflow, better, popular, supported, video, sensor, logos, images, unstructured, tsv, parquet, orc, json, csv, avro, file, lance, hudi, beta, delta, table, agnostic, regardless, format, using, will, support, kafka, pubsub, flink, fivetran, kinesis, airbyte, common, ingest, integrated, into, trino, starburst, spark, snowflake, presto, hive, dataproc, duckdb, dremio, cloudera, clickhouse, synapse, glue, emr, athena, supports, broadly, weka, vast, storagegrid, ontap, google, ecs, ceph, blob, adls, connects, uses, interface, adds, foundation, tech, partners, david, van, son, take, entire, weeks, implementing, half, stephen, seewald, raghvendra, verma, cory, matheson, easily, achieve, advanced, such, parallel, logic, conduct, compare, large, sets, ryan, green, cto, moving, solution, paid, off, quickly, few, days, completing, migration, already, testing, two, see, increases, vara, ghanta, principal, manager, allows, managing, versions, type, feed, files, tabular, tracking, feeds, pretty, fast, greg, forrest, director, foundations, transparent, traceable, repeatable, critical, important, don, just, focus, building, also, leonard, aukea, head, operations, adapted, accelerated, productivity, insight, holden, karau, source, saved, paralysis, overthinking, netflix, less, than, min, had, was, able, tests, against, validate, change, thoroughly, pushing, robustness, flexibility, systems, implemented, automated, cleaning, avoided, costly, duplication, established, robust, framework, powers, its, one, find, out, curious, efficiently, keep, gpus, busy, without, waiting, work, tool, remote, were, give, centralized, friction, create, debug, build, past, inputs, alongside, code, reproducibility, track, exact, runs, reproducible, instantly, roll, back, incidents, sandbox, pipeline, changes, zero, copy, enforce, standards, catch, errors, they, reach, simplify, regulatory, audits, evidence, manual, reporting, risk, controlled, capture, trail, lineage, automatically, enable, design, whitepaper, proof, clock, ticking, highly, scalable, manages, lifecycle, provenance, unified, bridging, gap, register, webinar, october, governing, autonomous, partner, sales, watch, demand, leaders, contracts, webinars, ebooks, guides, github, sample, notebooks, quickstart, experiments, agentic, announcement, acquires, dvc, uniting, pioneers, accelerate, skip, content,

Text of the page (random words):
the control plane for ai ready data lakefs skip to content lakefs acquires dvc uniting data version control pioneers to accelerate ai ready data read the full announcement product close product open product lakefs the control plane for ai ready data solutions close solutions open solutions use cases agentic ai data management ml experiments ai governance and compliance technologies openshift ai iceberg developers close developers open developers learn quickstart docs sample notebooks community github slack resources close resources open resources blog case studies ebooks and guides webinars ai ready data summit learn data version control data quality mlops data contracts learn from ai ml data leaders from dell lockheed martin red hat more on demand watch now pricing close pricing open pricing pricing contact sales book a demo company close company open company about us partner newsroom careers 5 2k book a demo try lakefs 5 2k book a demo try lakefs webinar october 22 governing autonomous ai agents with lakefs minio register bridging the ai infrastructure gap the control plane for ai ready data built on our highly scalable data version control architecture lakefs manages the data lifecycle provenance and unified access for ai and data engineering teams book a demo try lakefs trusted by the ai compliance clock is ticking is your data infrastructure ready learn how built in proof preventive controls and isolated data access make you audit ready across every workload and agent action read the whitepaper enable compliance and governance by design capture data audit trail and lineage automatically across every workload manage controlled and isolated data access across tools agents and users reduce compliance risk with preventive data controls simplify regulatory audits with built in evidence not manual reporting ensure data quality enforce data quality standards to catch errors before they reach production test pipeline and model changes in isolation on production data with zero data copy run agents in isolated data sandbox instantly roll back from data incidents make training and agent runs reproducible track the exact data used in every experiment training run or agent action version data alongside code and models for end to end reproducibility re create debug or build on any past result or agent run with the same inputs reduce data access friction give tools users and ai agents centralized access to distributed data work with any tool on remote data as if it were local keep your gpus busy without waiting for data curious how lakefs can help you deliver ai projects faster and more efficiently talk to one of our experts and find out case study how arm powers its data management infrastructure with lakefs with lakefs arm implemented automated data cleaning avoided costly data duplication streamlined engineering workflows and established a robust governance framework to manage data across distributed teams the result faster go to market reduced storage costs improved development velocity and stronger data governance read full case study faster go to market improved development velocity reduced storage costs stronger data governance lakefs saved us from the analysis paralysis of overthinking how to test new software on our data lake at netflix scale in less than 20 min i had lakefs up and running and was able to run tests against my production data in isolation and validate the software change thoroughly before pushing to production with lakefs we improved the robustness and flexibility of our data systems holden karau open source engineer with lakefs we have streamlined data science and mlops workflows adapted data access controls for different teams accelerated productivity and reduced time to insight for ml engineering projects leonard aukea head of ml engineering operations transparent traceable and repeatable development of ai is critical to us what s important for lockheed martin is that we don t just focus on what we re building but also on the how greg forrest director of ai foundations lakefs allows managing versions for any type of feed some files are tabular some are not tracking feeds in lakefs is pretty fast vara ghanta principal software engineering manager moving to a data branching solution has paid off quickly for us a few days after completing the migration we ve already reduced testing time by 80 on two different projects and we re excited to see how data branching increases our product velocity ryan green cto with lakefs we can easily achieve advanced use cases with data such as running parallel pipelines with different logic to experiment or conduct what if analysis compare large result sets for data science and machine learning and more stephen seewald raghvendra verma cory matheson it used to take our entire ml engineering team 2 weeks to launch 2 3 new models after implementing lakefs we now launch 6 new models in the same time with half the team david van son software engineer our partners seamlessly integrate with your data and ai stack lakefs object storage compute engines ingestion streaming data storage formats orchestration workflow ai ml data quality lakefs object storage compute engines ingestion streaming data storage formats orchestration workflow ai ml data quality lakefs adds the foundation for ai ready data to your ai and data tech stack lakefs connects to every object storage that uses the s3 interface amazon s3 azure adls azure blob storage ceph dell ecs google cloud storage minio netapp ontap netapp storagegrid vast data weka local storage lakefs supports all broadly used compute engines aws athena aws emr aws glue azure synapse clickhouse cloudera databricks dremio duckdb gcp dataproc hive presto snowflake spark starburst trino all common ingest technologies are integrated into lakefs airbyte aws kinesis fivetran flink gcp pubsub kafka lakefs is formats agnostic regardless of the format you re using lakefs will support it table formats delta lake beta hudi iceberg lance file formats avro csv json orc parquet tsv unstructured images logos sensor data video manage orchestration and workflows better with popular orchestration tools supported on lakefs airflow argo wfs dagster dbt kubeflow lakeflow declarative pipelines metaflow nextflow prefect seqera seamlessly integrate with lakefs with whatever your ml stack includes amazon bedrock agentcore aws sagemaker dask databricks dataiku dataloop datarobot domino labs e2b hex hugging face datasets jupyter labelbox lancedb mlflow pandas python r ray red hat openshift ai scale snorkel vertex ai w b data quality is mandatory for your data lake health ensure maintain the highest data quality together with lakefs anomalo bigeye deequ great expectations griffin monte carlo data try lakefs explore docs learn more about lakefs and ai ready data best practices case studies data engineering machine learning ai ready data anywhere a new architecture for control access and infrastructure read more how lakefs attimis onebucket and seagate exos bring together data control global access and on prem infrastructure to deliver trusted distributed ai ready data product thought leadership lakefs named a representative vendor in the 2025 gartner market guide for dataops tools read more we re excited to share that lakefs has been named a representative vendor in the 2025 gartner market guide for dataops tools we when agents touch production data read more according to dun bradstreet ai momentum survey 97 of organizations have active ai initiatives but only 5 say their data is adequately how department of energy ensures proper data governance for ai model development read more this case study is a summary of the talk presented at data ai summit 2024 project alexandria a digital library for research data lakefs named a representative vendor in the 2025 gartner market guide for dataops tools read more lakefs named a representative vendor in the 2025 gartner market guide for dataops tools read more when agents touch production data read more how department of energy ensures proper data governance for ai model development read more need help getting started talk to a lakefs engineer cloud docs blog community careers about us newsroom contact us cloud docs blog community careers about us newsroom contact us copyright all rights reserved privacy policy privacy settings terms of use do not share or sell my personal information pick up the slack with lakefs join our community of experts introduce yourself share your knowledge and discover best practices from fellow peers join us