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How Parallel helps Kepler build AI that finance professionals can actually trust. This post was originally published on Parallel's blog. Kepler is building AI for work where the answer can't just be plausible - it has to be right. Its first product, Kepler for Finance, helps investment professionals analyze public companies with institutional depth and AI speed. Analysts ask complex questions in natural language and receive answers backed by financial filings, computed metrics, and citations down to the page and line item. Achieving that level of reliability requires a different architecture from most AI systems. Kepler integrates Parallel's Search API as the discovery layer at the top of its analytical pipeline, combining AI's ability to understand open-ended questions with deterministic infrastructure that guarantees accuracy and auditability on the back end. Key impact. * Landscape discovery in minutes: Preliminary research that once took analysts days now runs as an automated pipeline step. * Expanded product capability: Kepler now supports competitive landscape and sector-level analysis, not just single-company research. * Global coverage: Discovery across private companies, international players, and niche sectors beyond curated databases. * Fully automated workflows: Parallel search results feed directly into Kepler's deterministic pipeline without manual extraction. In finance, reliability is architectural. Language models are excellent at interpreting questions, understanding context, and structuring answers. They're far less reliable at retrieving precise data or producing the same answer twice. In many applications, that tradeoff is acceptable. In finance, it isn't. A wrong number can mean a blown deal, a compliance issue, or reputational damage that lasts years. Kepler built the platform around that constraint. The architecture enforces a strict separation between two layers: an AI layer that interprets questions and structures answers, and a deterministic layer that retrieves financial data, computes metrics, and generates citations tracing every number to its source. The two communicate through structured interfaces, but they never blend. Today, Kepler for Finance covers 950K+ SEC filings, 14K+ companies, and 27 global markets. But even this architecture has a gap at the very top of the funnel. Every analysis starts with discovery, and that requires the open web. Most financial analysis doesn't start with a known list of companies. An analyst working on a deal typically starts with a question: * What does the competitive landscape look like around this company? * Which international players matter that a US coverage list might miss? * Which upstream suppliers could influence risk? There's no filing to retrieve yet - the analyst first has to determine what the analysis should even cover. Traditionally, that means scanning industry reports, asking colleagues, and searching the web before the real work begins. It's slow, inconsistent, and impossible to scale. Discovery is the only place in Kepler's architecture where the system permits probabilistic outputs. That makes the quality bar unusually high: if discovery surfaces the wrong companies, the entire downstream pipeline operates on incomplete context. Parallel's Search API met the bar: relevant, broad, and built for machines. Kepler evaluated discovery solutions across three requirements: * Relevance: Discovery has to be accurate enough that the downstream pipeline is always pointed at the right material. * Breadth of index: Its customers increasingly work across areas curated datasets struggle to cover - private companies, international competitors, niche industry segments. Parallel's coverage across the open web lets Kepler discover entities well beyond traditional financial databases. * Programmatic design: Most search products are designed for humans. Kepler needed structured outputs that route directly into its pipeline without manual extraction. "We built Kepler to be audit-ready at every step. That standard applies to discovery too. Parallel's accuracy and coverage are what made it the only search API we trusted in that role." - Vinoo Ganesh, CEO, Kepler When an analyst asks a landscape-level question, Parallel performs entity discovery using real-time information from the open web. Those results flow directly into Kepler's deterministic pipeline. From that handoff forward, no probabilistic system touches the data. Parallel identifies who matters. Kepler determines what the data says about them. What this unlocked. Before Parallel, Kepler was a research tool that needed to be provided an explicit list of companies - powerful, but limited to situations where analysts already knew which companies to analyze. * Competitive landscape analysis. Analysts can now start with broad questions like "What does the competitive landscape look like in this sector?" Parallel identifies the relevant companies; Kepler analyzes them. * Supply chain and sector mapping. For an analyst researching EV battery manufacturers, the most relevant upstream suppliers - cathode material producers across South Korea or China - often don't appear clearly in US filings. Parallel surfaces these entities so Kepler's pipeline can incorporate them. * Comp set construction in unfamiliar sectors. Investment professionals are frequently staffed on deals outside their primary coverage. Parallel enables Kepler to generate structured company sets dynamically, helping analysts understand the ecosystem around a target much faster. The architecture scales beyond finance. Kepler started in finance, but the architecture is domain-agnostic. Legal research, regulatory compliance, healthcare analysis, procurement intelligence - anywhere professionals need defensible decisions from verified information, the same problems exist. Discovery at the top of the funnel. Verifiability at every step downstream. Kepler is partnering with Parallel to bring this architecture to every domain where auditability is essential.

Daily Indian funding roundup & key news - 13th November 2025: Parallel Web Systems raises $100 Mn, Brandworks secures $11 Mn, mahindra-manulife JV announced & more. India's startup ecosystem witnessed strong investor momentum on 13th November 2025, with significant funding rounds across AI, space-tech, electronics manufacturing, and EV infrastructure sectors. The day's highlights include Parallel Web Systems' $100 million Series A round led by Kleiner Perkins and Index Ventures, Brandworks Technologies' $11 million Series A funding, and several promising early-stage investments in experience-tech, rocket propulsion, and event management. Meanwhile, a major joint venture between Mahindra & Mahindra and Manulife marked a key development in India's financial services landscape. Daily Indian funding roundup - 13th November 2025. | Company | Amount | Round | Lead investor(s) | Sector | | Alive | INR 6 Cr | Seed | Powerhouse Ventures | Experience-tech / Lifestyle | | Trishul Space | INR 4 Cr | Pre-seed | IAN Angel Fund | Space-tech / Rocket propulsion | | Event Planet Technologies | USD 250 K | Angel | Virendra Prasad | Event & wedding services platform | | Parallel Web Systems | USD 100 Mn | Series A | Kleiner Perkins; Index Ventures | AI / Web search infrastructure | | ACS Energy | INR 11 Cr | Pre-seed | Inflection Point Ventures (IPV) | EV charging infrastructure | | Brandworks Technologies | USD 11 Mn | Series A | Cactus Partners; Roha Family Office | Electronics manufacturing / R&D | Alive powers India's experience economy. Experience-tech startup Alive has raised INR 6 crore in seed funding to expand its curated experiences platform. Focused on travel, lifestyle, and live entertainment, Alive aims to make memorable experiences easily accessible through technology-driven discovery and booking tools. The startup has seen rapid traction over the past year, achieving exponential growth in both user base and revenue, and now plans to strengthen its partner network across major Indian cities. Trishul Space ignites India's private space ambitions. Prayagraj-based Trishul Space secured INR 4 crore in a pre-seed round led by IAN Angel Fund. The startup is developing next-generation liquid rocket engines and propulsion systems designed for small satellite launch vehicles. The funds will be used for R&D, prototype development, and testing facilities. By focusing on reusable and cost-efficient propulsion technology, Trishul Space aims to contribute to India's growing private space sector. Event Planet Technologies expands globally. Event Planet Technologies, a tech-driven event management platform, has raised USD 250 K in an angel round. The company simplifies large-scale event and wedding planning by connecting vendors, venues, and service providers through a single platform. With this funding, the startup plans to enhance its AI-based matching system, expand operations in Southeast Asia, and strengthen its backend technology for international scalability. Parallel Web Systems reimagines ai-first search. Founded by former Twitter CEO Parag Agrawal, Parallel Web Systems has raised USD 100 million in Series A funding from Kleiner Perkins and Index Ventures. The company is building AI infrastructure that allows intelligent agents and applications to access real-time web data securely. The funding will fuel product development, talent hiring, and global expansion as the company positions itself at the forefront of AI-powered web intelligence. ACS Energy charges India's EV revolution. ACS Energy raised INR 11 crore in a pre-seed round led by Inflection Point Ventures to accelerate the deployment of its smart EV charging infrastructure. The startup specializes in UPI-enabled public charging stations integrated with AI-based energy management systems. It aims to install over 5,000 charging points across India in the next 18 months, focusing on high-density urban areas and commercial properties. Brandworks Technologies boosts electronics innovation. Mumbai-based Brandworks Technologies has secured USD 11 million in a Series A round led by Cactus Partners and the Roha Family Office. The company designs and manufactures high-performance electronic products, IoT devices, and consumer tech components. The capital will be used to expand R&D facilities in India and Taiwan, enhance manufacturing capabilities, and develop next-generation hardware solutions for AI-driven devices. Key business news for 13th November 2025. Major JV: Mahindra & Manulife form life-insurance partnership. Mahindra & Mahindra Ltd. (M&M) and Manulife Financial Corporation have entered into a 50:50 joint-venture agreement to enter the life-insurance business in India, subject to regulatory approval. Must have tools for startups - recommended by startuptalky. * Convert Visitors into Leads- SeizeLead * Website Builder SquareSpace * Manage your business Smoothly Google Business Suite

AI startup Parallel Web Systems, founded by former Twitter CEO Parag Agrawal, has secured $100 million in Series A funding.