Barclays
Circuit mix
Where Barclays shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Software engineering & trading tech45%10 events
- Python & R data science23%4 events
- Cloud providers14%3 events
- Enterprise, analyst & AI expos9%2 events
- Vendor flagships & roadshows5%1 event
- AI engineering & MLOps5%1 event
Presence by conference and year
Each cell is one conference in one year. Fill shows the company sponsored, shaded by its best tier that year; a dot means it had speakers there. Hover for details; click to open the event.
- Title
- Platinum
- Gold
- Silver
- Bronze
- Other / unlabeled tier
- Had speakers
| Conference | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 | 2028 |
|---|---|---|---|---|---|---|---|---|---|---|
| STAC Summit | ||||||||||
| AWS re:Invent | ||||||||||
| PyData | ||||||||||
| The AI Summit | ||||||||||
| Databricks Data + AI World Tour | ||||||||||
| MLOps World (Machine Learning in Production) |
Activity by year
Three measures on one year axis; each panel has its own scale. 2027, 2028 is still mostly ahead, so its bars are faded and incomplete.
Conferences present at
Distinct conferences each year, split by whether the company sponsored or only had speakers there.
- Sponsored
- Speakers only
Distinct speakers
People from this company on a program that year, each counted once.
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Platinum
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 1 conference in 2019.
Counted per conference. 2026 is the latest year whose conferences have mostly happened. Tiers use the best tier each year; swatches show the path, oldest first. A conference counts as pulled out only when a later event published a complete sponsor list, since most events don’t say whether their list is complete.
Once or on and off 1
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- PyDataonce, 2019, Platinum
Lookalikes
Companies with the most similar conference footprint: they sponsor and speak at the same conferences. Bars are cosine similarity, from 0 (nothing shared) to 1 (identical).
- E.ON0.73
- BP0.73
- Ocado Technology0.73
- Millennium Management0.67
- CVS Health0.66
- Pluralsight0.63
- Morgan Stanley0.62
- ASAPP0.62
8 Cluster: PyData · posit::conf circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 1 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| Balsamiq | 1 | 100% |
| Coding Blocks | 1 | 100% |
| Elastic | 1 | 100% |
| Go-Jek | 1 | 100% |
| IIIT-D ACM Student Chapter | 1 | 100% |
| O4S | 1 | 100% |
| Onepanel | 1 | 100% |
| Python Software Foundation | 1 | 100% |
| Sketch | 1 | 100% |
| Sticker Mule | 1 | 100% |
Neighborhood: companies with nearby conference footprints
Barclays (ringed) and the 30 companies closest to it on the company map. Close together means they sponsor and speak at many of the same conferences. Distances are only meaningful locally; the axes have no meaning. Dot size: conferences present at. Color: cluster.
Sponsorships 1
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| PyData Delhi 2019 | Aug 3–4, 2019 | New Delhi, India | Platinum | Platinum |
Speakers 26
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Corey Cederquist | AWS re:Invent 2026 | breakout | From Gen AI to Agentic AI: Transforming Finance Operations on AWS with Barclays (sponsored by Capgemini) | — |
| Kristen Bennie | AWS re:Invent 2026 | breakout | 3-step blueprint for scaling AI with a modern enterprise core (sponsored by IBM) | — |
| Hariom Tatsat | STAC Summit New York, Fall 2026 | speaker | Beyond the black-box: Interpretability of Agentic AI | — |
| Vivek Dak | The AI Summit London 2026 | keynote | — | — |
| Ariye Shater | STAC Summit New York, Fall 2025 | speaker | Beyond the black box: Interpretability of LLMs in finance | — |
| Meggy Chung | Data + AI World Tour London 2025 | keynote | Keynote | — |
| Amit Nandi | STAC Summit London, Spring 2025 | panelist | License to operate: Expanding MLOps for the Agentic era | — |
| Baranidharan Sivapatham | STAC Summit Singapore, Spring 2025 | panelist | Show me some love: Improving the FPGA “Engineer Experience” | — |
| Sapna Sardana | AWS re:Invent 2024 | breakout | “Black swan” vs. “green swan”: Powering sustainability with data & AI (sponsored by Capgemini) | Video |
| Sumit Dahiya | 5th Annual MLOps World and Generative AI World Conference 2024 | speaker (virtual) | Secure and Scalable MLOps Pipelines for Generative AI in Cloud-Native Architectures | — |
| Aaron Byrne | PyData London 2024 | talk | Training and Deployment of ML models at scale in a Risk Controlled Banking Environment | — |
| Baranidharan Sivapatham | STAC Summit Asia (Singapore), Spring 2023 | speaker | FPGAs beyond ultra-low latency? | — |
| Pawel Szopinski | STAC Summit New York, Fall 2022 | speaker | Low-latency market integration: Time to rethink buy-vs-build? | — |
| Richard Croucher | STAC Summit London, Spring 2022 | speaker | Will data volume destroy trading economics? | — |
| Pawel Szopinski | Global STAC Live, Fall 2020 | speaker | DPDK: A multi-purpose tool for realtime business | — |
| Pawel Szopinski | Global STAC Live, Spring 2020 | speaker | Infrastructure management as an unfair advantage | — |
| Richard Croucher | Global STAC Live, Spring 2020 | speaker | Latest learnings on memory & storage | — |
| Vojtech Kral | AWS re:Invent 2019 | breakout | Barclays: Accelerating research data science using AWS | Slides · Video |
| William McWeeny | AWS re:Invent 2019 | breakout | Barclays: Accelerating research data science using AWS | Slides · Video |
| Petr Wolf | PyData New York City 2019 | speaker | From Raw Recruit Scripts to Perfect Python (in 90 minutes) | Video |
| Stanley van der Merwe | PyData New York City 2019 | speaker | From Raw Recruit Scripts to Perfect Python (in 90 minutes) | Video |
| Mayank Jain | PyData Delhi 2019 | sponsor | Predicting Real-Time Transaction Fraud Using Python and spark (Sponsored Talk) | — |
| Pankaj Gupta | PyData Delhi 2019 | talk | Improving Model Lifecycle Management for Machine Learning Models | — |
| Filip Ter | PyData London 2019 | tutorial | Data Analysis in Parallel | — |
| Ashok Vaswani | The AI Summit London 2019 | keynote | — | — |
| Richard Croucher | STAC Summit London, Spring 2019 | speaker | Compute, meet Data: Accelerating I/O at the micro and macro level | — |