(SES) SES AI Corporation Business Model Canvas Research

SES AI Corporation collaborates with research labs and universities to advance battery science, using academic partners to validate new materials, test safety, and refine analytical methods. These ties speed technology proof points and give SES AI Corporation access to specialized PhD-level talent, which matters as it pushes next-gen Li-Metal and AI-driven battery R&D.

• Materials discovery support
• Safety testing and validation
• Analytical method development
• Talent access from academia

SES AI Corporation relies on cloud data and AI tooling to speed battery design, cutting the loop from idea to test. Computational partners help train models, run simulations, and screen materials at scale, so the company can iterate faster and spend less on lab trials.

• Faster model training
• Higher-volume simulation
• Materials screening at scale
• Lower experiment cost

SES AI Corporation uses computational methods and AI to screen chemistries and optimize formulations, cutting lab trial-and-error and speeding development cycles. That shift improves hit rates by narrowing the search space before physical testing, so teams can focus on the most promising battery materials faster.

• Screen chemistries digitally first
• Reduce lab trial-and-error
• Improve speed and hit rates

SES AI Corporation supports customer qualification by helping enterprise buyers test cells, review data, and handle integration work through commercialization. This matters because enterprise battery sales can take 12 to 24 months of validation, so technical support is a core activity, not a side task.

• Customer testing support
• Data review for qualification
• Integration help through launch
• Long enterprise sales cycle

The work reduces risk for customers moving from pilot to production, where each step can delay revenue and shipment timing.

SES AI Corporation needs specialized battery lab equipment for cell assembly, characterization, and test runs, because fast learning depends on fast build-measure cycles. In 2025, this kind of lab setup is what turns R&D spend into higher throughput and tighter quality control across more prototype iterations.

• Rapid cell assembly
• Precise quality measurement
• Higher experiment throughput

SES AI Corporation’s AI and data models are a key resource because the company’s battery R&D gets stronger as it adds proprietary experimental data and retrains its models. That creates compounding learning effects: each test round can improve prediction quality, cut trial-and-error, and make future battery designs faster and better.

• Proprietary data improves model accuracy over time
• Trained models speed battery development
• More experiments can strengthen the moat

SES AI Corporation’s advanced battery safety aims to improve thermal stability and operational safety versus legacy lithium-metal and lithium-ion designs, which is critical for automotive qualification and scale-up. In EVs, battery fires remain a major barrier: U.S. NHTSA recorded 58,233 fire incidents in 2024, underscoring why safer cells matter.

• Higher thermal stability
• Safer automotive qualification
• Supports scale-up readiness

SES AI can tailor cell design for specific performance, size, and weight needs, which matters most in automotive and other high-value uses. That flexibility fits a market where global EV sales reached 17.1 million in 2024, so makers need cells that match tight packaging and engineering targets, not one-size-fits-all formats.

• Tailors cells to exact specs
• Supports automotive packaging needs
• Helps high-value use cases

SES AI uses pilot programs to prove battery performance in real customer conditions before scale, so buyers can test safety, energy density, and cycle life with lower adoption risk. These pilots also generate decision data for procurement and engineering teams, making proof before scale the core of the relationship.

• Real-world proof before volume orders
• Lower adoption risk for customers
• Decision data from live testing

SES AI Corporation’s customer relationships are built around multi-year supply and technology roadmaps, because battery buyers usually demand continuity, quality, and volume readiness before they switch suppliers. That makes retention a trust game: once a program is in place, the goal is to keep performance steady through 2025-2026 and avoid disruption.

• Multi-year roadmap alignment
• Continuity and quality first
• Volume readiness supports retention

SES AI uses battery and mobility conferences in 2025/2026 to show its technology to automakers, cell makers, and other buyers, while meeting leads face to face. These events lift visibility, build credibility, and help turn interest into a sales pipeline.

• Show technology to qualified buyers
• Build trust with live demos
• Generate leads and pipeline

SES AI Corporation’s website and public filings turn technical progress into clear B2B discovery cues, helping buyers track cell development, partnerships, and commercialization steps. These channels also educate customers and raise market awareness; as of the latest filings, SES AI Corporation still reported limited revenue and a strong focus on R&D-led execution.

• Shows technical milestones
• Supports customer education
• Builds market awareness
• Fits B2B discovery

Advanced aviation and drone developers need lightweight, high-energy cells that cut takeoff weight and extend flight time. SES AI Corporation’s fit here is in specialty mobility demand, where buyers value energy density and fast power delivery more than low-cost, general-purpose batteries.

• Lightweight cells support longer range.
• High power delivery helps takeoff and climb.
• Energy density is the key buying test.

Industrial and specialty users include robotics and specialty equipment makers that need cells built for custom form factors and duty cycles, not just standard packs. These buyers prize high power, long cycle life, and fit-for-purpose designs in high-performance use cases.

• Robotics needs custom sizes.
• Duty cycles vary by use.
• Specialty tools need high power.

Modern battery R&D makes cloud and compute a real digital infrastructure cost for SES AI Corporation, because AI model training and simulation need heavy GPU capacity. That compute helps screen chemistries faster and optimize cell designs, which matters when development cycles depend on quick, data-rich testing.

• AI training raises cloud spend
• Simulation speeds screening
• Compute supports battery optimization

SES AI Corporation’s SG&A and compliance cost base rises with corporate overhead, legal work, and regulatory reporting. As a public company, it must fund SEC filings, audit, controls, and disclosure work, and commercial qualification for customer programs adds testing, documentation, and coordination costs.

• Corporate overhead lifts fixed costs
• Public-company reporting adds expense
• Legal and regulatory work is ongoing
• Commercial qualification needs cash too

Milestone payments let SES AI Corporation collect cash when customers or partners complete technical gates, such as prototype validation or sample approval. That phased setup supports commercialization step by step and lowers risk for both sides because payment follows proof of progress.

• Paid on technical stage completion
• Shares risk across both sides
• Fits phased commercialization

SES AI Corporation can use grants and collaborative funding as non-dilutive capital from government or research programs, plus university or industry partners. These funds help pay for advanced R&D, pilot testing, and strategic innovation without adding equity dilution.

• Non-dilutive cash from grants
• Supports advanced R&D work
• Funds strategic innovation programs