Klarix Intelligence Engine

Build a first-pass candidate list from hundreds of thousands of pre-profiled B2B companies using Voyage 4 semantic vector embeddings. Ranks accounts by topical similarity to an ICP description, tech stack, business model, and vertical, then screens the retrieved candidates for buyer-vs-vendor role and corporate status and reports what it withheld. Returns a candidate net, not a qualified list: the similarity figure is not a fit score, and every account should go through score_prospect_fit before outreach.

Score a company against your ICP on five weighted axes — Strategic Fit, Tech Alignment, Buyer Persona Readiness, Growth Triggers, and Landmine Risk — each 1-10, with a weighted overall and a 7+/10 pursue threshold. Uses live public web evidence and cites every claim. Curate the score to your own business with our_company_name, our_domain, our_differentiators, or a Klarix client_id — a client_id also supplies the ICP, so icp_description becomes optional. Judges roles, never individuals; returns no contact details.

Build a live sales battlecard for a competitor domain: SWOT from their point of view, the gap between their marketing claims and buyer-reported reality, and concrete landmines with spoken talk tracks. Every claim cites a public source. Optionally aim it at a target vertical, and curate it to your own business by passing our_company_name, our_domain, our_differentiators, or a Klarix client_id — landmines and talk tracks then become lines your seller can actually defend.

Compare YOUR company against a specific competitor or incumbent you want to displace. Researches both sides on the live public web, then returns asymmetric advantages (where you win structurally), their defensive moats (where to stop arguing), a fixed four-dimension comparison matrix (Pricing, Tech / Delivery Speed, Quality Floor, Support / Customization), spoken talk tracks and landmines for a live evaluation, and a three-step displacement strategy. Identify your side with our_domain, our_company_name, or a Klarix client_id. Any claimed advantage the evidence does not support is reported back rather than repeated.

Synthesize an executive one-pager on a company from live public web sources: snapshot, findings per requested focus area, dated buying signals, deal risks, and stated unknowns. Every claim carries a source URL. Focus areas include pricing, leadership (roles only), recent_events, tech_stack, customers, hiring, funding, products, and risks.

Write cold outreach that opens on a researched, dated insight about the prospect rather than a pleasantry. Supports a 3-step email sequence, a 3-step LinkedIn sequence, or 6 multivariant openers. Enforces the Klarix voice contract (banned AI words and phrases, punctuation tells, rhythm) and reports any violations. Writes to a job title, never to an individual, and never emits contact details.

Deep multi-source web crawl into a four-quadrant SWOT matrix for a company: internal strengths (moat, proprietary tech, distribution lock) and weaknesses (pricing friction, customer complaints, legacy tech), plus external opportunities (untapped verticals, market vacancies, adjacent expansion) and threats (substitutes, price commoditization, regulatory shifts). Every entry carries evidence and a consequence. Adds strategic exploit vectors for winning deals against them and defensive counter-plays. Curate it to your own business with our_company_name, our_domain, our_differentiators, or a Klarix client_id so every vector is one you can actually execute. Returns markdown plus structured JSON.

Exhaustive intelligence probe on a company across five dimensions: firmographic and corporate evolution (funding, revenue tier, team growth), product and technology teardown (stack, API presence, core capabilities), leadership and organizational signals (executive hires, board composition, departures — publicly reported executive names allowed when cited, never contact details), active buying and growth triggers (hiring surges, expansion, product launches), and risk analysis with explicit unknowns. Every finding carries a source citation and an implication. Defaults to depth "standard", which returns a tighter, higher-quality citation list; request "comprehensive" when maximum coverage matters more than citation density.

Retrieve verifiable academic and engineering literature for a technical topic so a claim can cite a resolvable DOI instead of a vendor blog post. Queries Semantic Scholar (citation graph, abstracts, open-access PDFs) and the arXiv preprint index, merges duplicates, and ranks by citation count then recency. Returns title, authors, year, DOI / arXiv URL, citation count, and an extractive key finding taken verbatim from the abstract. Keyless; set SEMANTIC_SCHOLAR_API_KEY to escape the shared anonymous rate limit.

Map a competitive landscape for an industry or vertical from live public sources: Tier-1 incumbents against emerging disruptors, category positioning quadrants with the white space in each, published pricing models and price bands, and the narrative themes that dominate zero-click and AI answers — including which themes are still open. Ends with buyer shifts and defensible entry wedges. Returns a landscape matrix in markdown plus structured JSON.

Map the internal buying committee (Economic Buyer, Champion, Technical Evaluator, Procurement) for an account with title patterns, pain points, objections, and multi-threading strategy.

Detect recent account inflection points (leadership changes, funding, hiring surges, product updates, regulatory events) within a timeframe.

Deconstruct an account's technical infrastructure, dev tools, cloud providers, AI/data stack, and identify displacement vulnerabilities.

Generate an end-to-end competitive displacement playbook with switching cost mitigations, POC blueprints, and migration timelines.

Deconstruct a physical hardware device, battery pack, medical system, or software API into an institutional-grade technical specification table with exact units, tolerances, verified images/diagrams, datasheet links, certifications, and displacement seams.