New AI tool brings transparency to the solar buying process

The residential solar sector has long suffered from pricing inconsistency and aggressive sales tactics. While the utility sector undergoes massive technical innovation, individual homeowners are often left navigating a market that feels like a black box. This disconnect is what drove Tursun Ablekim, founder of AgentSolar AI and an alumnus of the National Renewable Energy Laboratory (NREL) and First Solar, to launch a platform designed to bring transparency to the industry. 

Ablekim’s journey began with a simple realization. During his time at NREL and First Solar, he worked on the cutting edge of PV technology to squeeze out minor efficiency gains. However, he soon noticed a massive disconnect at the last mile of solar adoption. 

“What is the point of a scientist spending years making a solar panel 1% more efficient if those gains are immediately wiped out by a sales process that adds 30% or 40% in ‘soft costs’ to the final price?” Ablekim asks. “We don’t have a hardware problem; we have an information and efficiency problem.” 

After gathering and analyzing over one million data points, Ablekim discovered that U.S. homeowners overpaid by an estimated $2 billion in 2025 compared to fair market prices. He refers to this massive premium as an unnecessary “sales-rep tax” on the energy transition. 

To combat this, AgentSolar AI was developed to act as an active, automated advocate for the consumer. Unlike traditional, passive chatbots that merely offer basic price-per-watt estimates, AgentSolar relies on agentic AI to take action on behalf of the user. The platform’s Quote Evaluation Agent can ingest a 40-page proposal PDF, extract financial line items, and cross-reference them against a comprehensive market database. Meanwhile, its Company Research Agent cross-checks company histories and reviews to verify installer reputation. 

Crucially, the platform takes active steps beyond passive feedback. If a homeowner decides to move forward, the agent initiates a structured negotiation workflow, developing concrete counteroffers and sending automated emails to secure better terms. 

“It can handle multiple back-and-forth exchanges, and only when it determines that a truly fair deal has been reached does it notify the homeowner that the contract is ready to sign,” Ablekim explains. 

To maintain trust, every automated communication is reviewed by a human system admin, ensuring a balance between algorithmic efficiency and human oversight. This shifts the human’s role from doing grueling manual labor to providing high-level direction. 

This automation of the sales process could trigger a massive compression of solar soft costs, particularly customer acquisition. In the United States, acquiring a customer through door-knocking, lead buying, and high-pressure sales pitches can add $4,000 to $6,000 to an 8 kW system. Ablekim believes that as platforms like AgentSolar scale, these expensive customer acquisition costs will be the first to disappear. This shift will liberate regional and local installers who do quality work but lack the massive marketing budgets of national players. 

Ultimately, Ablekim envisions a future where the home energy journey is entirely autonomous. Within five years, AI could handle everything from initial roof modeling and quote negotiation to long-term post-installation monitoring and Virtual Power Plant management. Ablekim forecasts a residential market reshaped by specialized digital services, including a “Zillow for Solar” to bring data transparency to every roof and a “Manus for Solar” to offer autonomous execution. 

“We are excited to be part of this disruption,” Ablekim says, “driving the transition toward a more transparent, efficient, and agent-led future.”