EPAM and TGS Deploy AI‑Powered seismic Imaging on AWS, Accelerating Energy Data Workflows—a joint announcement that places a cloud‑native, AI‑enhanced seismic processing platform at the heart of the energy sector’s digital transformation. The collaboration brings TGS Imaging AnyWare® onto Amazon Web Services, promising faster, cheaper subsurface analysis for oil‑and‑gas operators grappling with ever‑growing data volumes.
What EPAM and TGS Announced
In a June 8, 2026 press release, EPAM Systems, Inc. (NYSE: EPAM) and TGS, a leading provider of energy data, confirmed that TGS Imaging AnyWare® is now running on AWS. The migration moves the core imaging workload from on‑premises hardware to elastic cloud instances, leveraging AWS Graviton processors and Spot pricing to cut compute costs while boosting throughput. EPAM’s Energy HPC Orchestrator (EHO) stitches together data ingestion, processing, and AI‑driven interpretation into a single, orchestrated workflow.
How the Platform Works
The revamped AnyWare solution rests on three pillars. First, TGS Data Verse, an OSDU‑compliant data‑as‑a‑service layer, streams petabyte‑scale seismic and well data directly to browsers, eliminating the need for local storage silos. Second, the imaging engine runs on AWS Graviton 2/3 instances, delivering up to 30 % performance gains on select processing steps while Spot instances drive up to 70 % cost reductions compared with on‑demand pricing. Third, EPAM’s EHO provides a composable workflow engine that can invoke AI models for velocity‑model building, fault detection, or attribute extraction, allowing users to AI‑driven interpretation and plug in new algorithms without rewriting the entire pipeline.
Why It Matters for Energy and AI
Energy companies are under pressure to turn subsurface data into actionable insights faster than ever. A recent Gartner survey found that 68 % of upstream firms plan to shift at least 30 % of their seismic processing to the cloud by 2027, citing scalability and cost as primary drivers. By moving to AWS, TGS reduces the latency between data acquisition and interpretation, enabling quicker drilling decisions and more efficient field development. The AI‑native architecture also opens the door for generative models that can predict missing data or suggest optimal acquisition parameters, a capability that traditional HPC clusters struggle to deliver.
Competitive Context
TGS’s cloud‑first approach competes directly with offerings from Schlumberger’s DELFI platform and Halliburton’s Landmark Cloud. While Schlumberger emphasizes an integrated SaaS stack, TGS differentiates itself through an open‑source‑friendly OSDU data layer and the ability to run custom AI models on AWS’s extensive marketplace of services, including SageMaker and Bedrock. Microsoft Azure’s energy‑focused cloud services also target the same market, but EPAM’s partnership brings a deep systems‑integration expertise that many pure‑play cloud vendors lack.
Implications for Enterprise Teams
For enterprise marketing and sales teams within the energy sector, the shift to an AI‑enabled cloud platform reshapes the buyer journey. Faster turnaround times mean that proof‑of‑concept deployments can be demonstrated in weeks rather than months, shortening sales cycles. Moreover, the subscription‑based pricing model of AWS Spot and EPAM’s managed services aligns with the growing preference for OPEX over CAPEX, simplifying budgeting for CFOs. Marketing messaging can now focus on tangible ROI—up to 40 % faster time‑to‑insight and up to 60 % reduction in compute spend—rather than abstract technology benefits.
Future Outlook
The migration is just the first phase. EPAM and TGS plan to embed large language models (LLMs) that can parse geological reports and automatically generate interpretation summaries, a move that would bring natural‑language AI into the core of subsurface analytics. As AI chips from Nvidia and custom AWS Inferentia accelerators become more prevalent, the platform is positioned to scale its AI workloads without a hardware refresh.
Market Landscape
The broader AI cloud market is consolidating around a few dominant ecosystems. Amazon Web Services leads with the deepest suite of AI services, while Google Cloud pushes generative AI and Microsoft Azure leans on its partnership with OpenAI. In the energy vertical, the convergence of AI, high‑performance computing, and data‑as‑a‑service is driving a wave of platform‑as‑a‑service offerings that promise to replace legacy seismic processing farms. IDC projects that by 2028, cloud‑based seismic processing will account for more than 45 % of total industry spend, up from under 15 % in 2023.
Top Insights
- Speed & Cost: AWS Graviton + Spot instances deliver up to 30 % faster imaging and up to 70 % lower compute costs versus traditional on‑prem HPC.
- Open Data Layer: TGS Data Verse’s OSDU compliance enables seamless data sharing across partners, reducing data‑staging time by an estimated 40 %.
- AI Integration: EPAM’s Energy HPC Orchestrator allows plug‑and‑play AI models, positioning the platform for future LLM‑driven interpretation workflows.
- Competitive Edge: By combining EPAM’s systems integration with AWS’s scale, TGS offers a more flexible alternative to closed SaaS stacks from Schlumberger and Halliburton.
- Enterprise Impact: Subscription‑based pricing and rapid proof‑of‑concept cycles shorten sales cycles and align with OPEX‑focused budgeting in the energy sector.
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