Brightwave, an agentic AI research platform built to help professionals understand the world’s most complex problems, has introduced research agents, enabling users to control fleets of research autonomous agents from a single, unified control plane. This release launches state of the art multi-agent research systems, transforming Brightwave into an IDE for information.
Inspired by system and user interface design patterns drawn from AI-powered software engineering tools like Cursor, Brightwave’s agentic technology allows the system to spawn long-running workers that can perform complex, open-ended tasks autonomously without interrupting users’ research flows.
- This technical approach enables Brightwave to infer a research plan from a user’s request, defining at inference time the sequence of activities required to accomplish a research goal, such as to creating a long-form deep research report, cloning a previously-authored document, refining and updating a document, or constructing an information-dense chart or evidence-linked table.
- Given a research plan, an asynchronous background agent uses a host of search, reasoning, fact checking, planning and presentation tools to accomplish that goal. Once the background agent believes it has accomplished its task, it submits its work product to an LLM judge, an independent system that uses powerful reasoning models to assess whether the output satisfies the original user requirements.
- Much like a software engineer would use unit tests to determine whether a piece of code satisfies a set of requirements, Brightwave uses these satisfaction criteria to ensure users receive high-quality, grounded research deliverables from every Brightwave interaction.
“The future of AI systems is all about deliverables. AI’s impact on software engineering is a great example. Lightweight, asynchronous feedback on complex work products wins against close management every time,” said Mike Conover, CEO and Co-Founder of Brightwave.
With background agents, users can define a high-level research objective with succinct natural language instructions and the system reasons independently about what data sources should be considered. For example, Brightwave can prompt the platform for reports on the real estate and energy players likely to be positively impacted by a recent executive order on AI, and using data from sources like whitehouse.gov, public filings and regulatory disclosures, Brightwave will produce a visualization-rich deep research report asynchronously. From there, users can continue to ask clarifying questions, edit and refine the substance of the report itself, or deepen their understanding of the primary sources Brightwave has discovered.
“Brightwave has transformed my research process, cutting the time it takes to analyze earnings filings and call transcripts,” said Brightwave client, CIO at a billion-dollar family office. “By instantly extracting insights, flagging sentiment shifts, and surfacing long-term trends, Brightwave gives me back the time to focus on what matters most across the 200+ companies I cover: developing sharper, high-conviction investment theses.”
“We’ve been focused on realizing this vision since we started the company,” continued Conover. “From day one it was clear to our team that this type of autonomous research is where the market would go, and every engineering and product decision we’ve made is a reflection of that belief. That’s the reason Brightwave works better than any other product on the market – it was designed for this moment.”
Agentic is generally available, and new users can trial the platform directly for free—no enterprise contract required.
Thanks for reading CPA Practice Advisor!
Subscribe Already registered? Log In
Need more information? Read the FAQs
Simran August 13 2025 at 4:24 am
This is an exciting development in AI-powered research workflows. The ability to coordinate multiple autonomous agents asynchronously—and then have their outputs reviewed by an independent LLM judge—strikes a great balance between automation and quality control. I especially like the analogy to unit testing in software engineering; applying that rigor to research deliverables could be a real game-changer for decision-making in sectors like finance, law, and policy. At Serviiion.com, we see similar potential in using advanced AI tools to streamline complex compliance and reporting processes, giving professionals more time to focus on strategic priorities. Looking forward to seeing how Brightwave evolves as an IDE for information