Thordata
Fuel AI training with high-quality, scaled data via proxies
440 followers
Fuel AI training with high-quality, scaled data via proxies
440 followers
As AI training and real-time applications accelerate, high-quality data has become a critical bottleneck in the age of artificial intelligence. Thordata provides residential, mobile, and data center proxy infrastructure for AI teams and data-driven businesses, enabling reliable global web data collection, responsible regional access, and smoothly scalable long-term data pipelines. From the very beginning, Thordata has focused on performance, stability, and compliance.
Tate-A-Tate
Thordata
@eeeeeach If you have a moment, I'd be curious to know what specific markets or verticals you focus on. Hearing about your data needs helps us ensure we're building the right features for experts like you.
This looks perfect for our use case! Does it offer sticky sessions for multi‑step workflows like checkout simulations?
Thordata
@orman_canida yes, Thordata supports sticky sessions for multi‑step workflows like checkout simulations, login sequences, and cart monitoring. You can assign a dedicated residential or mobile IP to persist cookies, headers, and session tokens across multiple requests, exactly as a real user would.
Thordata
@orman_canida Yes, Thordata supports this.
@orman_canida Absolutely. Sticky sessions are available and commonly used by our users for complex workflows where consistency and session continuity really matter.
@orman_canida Yes — sticky sessions are supported, which makes a big difference for multi-step or stateful flows. Without that, a lot of realistic workflows just break down.
Typeless
Daily user here for competitive intelligence work. I used to build custom proxy solutions myself, but this service delivers far better value for the price. Highly recommended.
Thordata
@yuki1028 Thank you so much — coming from someone who has built and maintained their own proxy infrastructure, this means a lot. We built Thordata precisely for experts like you, who know the real cost of “DIY” not just in money, but in time, reliability, and focus. Hearing that it’s become a daily part of your competitive intelligence workflow is the best feedback we could hope for. We’re here to keep earning that trust.
Thordata
@yuki1028 We really appreciate you taking the time to share this. When users with hands-on proxy experience tell us we deliver better value, it validates the core mission: to turn proxy infrastructure from a time-consuming distraction into a reliable, scalable advantage. If you ever have suggestions from your daily use — whether on features, reporting, or integrations — please don’t hesitate to reach out. We’re committed to making Thordata the obvious choice for teams that depend on data.
@yuki1028 Really appreciate this feedback.
Competitive intelligence at scale is tough, and it’s especially meaningful coming from someone who understands the trade-offs of custom-built proxy solutions.
@yuki1028 Thank you — we really appreciate this. Feedback like this, especially from someone who’s built custom solutions before, is exactly who we’re building for.
Does the service work with our existing VPN/on‑prem egress? Can we chain proxies for extra anonymity?
Thordata
@ambrosex We're sorry, we don't currently support this.
BizCard
Been using Thordata for a month now. The residential proxy pool is incredibly reliable—our scraper success rate went from 40% to 98% overnight.
Thordata
@haoran_fok Thank you so much for sharing this fantastic feedback. It's incredibly rewarding for our entire team to hear that Thordata has made such a dramatic impact on your operations. A jump from 40% to 98% success rate overnight is exactly the kind of transformative result we built our residential proxy network to deliver.
@haoran_fok That’s amazing to hear — thank you for sharing real numbers. Reliability at scale is exactly what we optimize for, so seeing that kind of jump in success rate really validates the work the team has put in.
Hey everyone,
While my work is more about textures and floor plans than AI training, the underlying principle here makes perfect sense. For any tool that needs to source real-time product data, pricing, or material availability from around the web—especially from region-specific vendors—having reliable, compliant access to that information is crucial. A service that provides stable, scalable infrastructure for this kind of data collection would be a powerful enabler for building smarter, more informed design and sourcing applications. It addresses a fundamental need for any data-dependent service, creative or otherwise. Solid foundation.
Thordata
@anya_furnishd Thank you so much for this incredibly thoughtful perspective. You've beautifully articulated a vision we hold deeply: that robust data infrastructure shouldn't just exist for "tech" in the abstract, but to empower all disciplines—including and especially creative ones like yours.
@anya_furnishd Thanks for articulating this so clearly. At the end of the day, Thordata is about making web data a dependable input — no matter the industry or application.
@anya_furnishd Thank you for such a thoughtful perspective. You’re exactly right — regardless of the industry, once a product depends on real-time, region-specific data, reliable and compliant access becomes foundational. That’s the core problem we’re aiming to solve across many different use cases.
Data quality really is the hidden bottleneck for AI. Interesting focus on stability and compliance — reliable long-term pipelines matter much more than just raw proxy access. Curious how teams are using this in real-time AI workflows.
@shemith_mohanan This resonates a lot. From what I’ve seen, teams use it for things like real-time pricing signals, monitoring market changes, or feeding live context into AI systems — stability matters way more there than just raw access.
Thordata
@shemith_mohanan In practice, teams use Thordata in two key ways for real-time AI:
For live AI applications: Powering customer-facing tools (like chatbots, recommendation engines, or dynamic pricing systems) that need to fetch and process current data from external sources reliably, without being blocked or fed corrupted inputs.
For continuous training/validation: Maintaining a steady stream of fresh, high-fidelity data from target regions or sites to keep models accurate and aligned with real-world conditions over time—turning a static model into a living system.
It ultimately comes down to treating data ingestion not as an afterthought, but as critical, production-grade infrastructure. That’s the foundation that lets AI teams build with confidence for the long term.