AI assistant built for real estate teams that listens, coaches, and guides agents in real time to help them close deals with confidence.
AI assistant built for real estate teams that listens, coaches, and guides agents in real time to help them close deals with confidence.
Shilo is a paid, quote-based AI coaching assistant for real estate teams that listens to agent conversations, provides real-time guidance, analyzes and grades calls, supports training and role play, and helps managers improve follow-through without replacing the team's existing CRM or lead sources. The company positions the product for real estate agents, team leaders, brokerages, and high-volume teams that need more consistent sales conversations without replacing their existing CRM, transaction management system, or lead sources. Its public website describes Shilo as listening, coaching, and guiding agents in real time, and it presents real-time guidance, real-time call analysis, real-time call grading, transcripts, sentiment, coaching feedback, role play, and CRM enrichment as core capabilities. Pricing is not publicly listed; buyers are directed to book a demo, so exact plan cost, per-seat rate, seat minimum, call-volume allowance, usage cap, onboarding fee, implementation scope, support level, renewal term, and contract minimum must be confirmed with Shilo directly. For evaluation purposes, that means Shilo should be treated as a quote-based sales-led product rather than a self-serve SaaS tool with transparent monthly pricing. The product is positioned around a clear operational problem: growing real estate teams often have their best scripts, objection-handling methods, follow-up habits, call review processes, and manager coaching knowledge spread across team leaders, documents, call recordings, and recurring training meetings. Shilo aims to capture what happens in real conversations and turn those interactions into coaching, call review, agent training, role play, scorecards, transcripts, sentiment signals, and next-step support for agents and managers. The most verifiable public facts are that Shilo is real-estate-specific, it is sold through a demo motion, it emphasizes real-time call guidance and grading, it says it enhances rather than replaces CRMs and related real estate systems, and its current website messaging promotes customer-reported impact across 100+ teams plus an announced $2.6 million seed round. Those customer outcome claims should be read as vendor-published proof points rather than independently audited benchmarks. Feature claims such as live coaching prompts, call grading, CRM enrichment, and manager visibility are best validated during a demo against the buyer's actual phone system, CRM, lead sources, compliance needs, and coaching workflow, because the public site does not provide detailed technical documentation, integration matrices, exact transcription accuracy, model-training details, or implementation timelines. Shilo is therefore strongest for real estate organizations with enough call volume and management structure to benefit from standardized coaching, faster agent ramp-up, and more complete call follow-through, while smaller teams should confirm whether the sales-led package and implementation effort match their scale.
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Shilo describes real-time call analysis and guidance for real estate teams. The website positioning indicates that transcription and conversation understanding support live coaching, post-call review, and CRM follow-through, but the provided source context does not verify exact latency targets, benchmark performance, or independently measured transcription accuracy.
During active calls, Shilo is positioned as providing real-time guidance for agents, including support around conversation quality and objection handling. The product messaging supports the existence of live coaching assistance, but the provided source context does not verify the exact interface format, the size of any objection library, or the number of prebuilt coaching prompts.
Shilo's AI assistant is described as helping teams learn from calls, role play, train, and improve follow-up quality. Its recommendations are positioned as relevant to real estate conversations and team workflows, but the provided source context does not verify a required minimum call volume, the exact training process, or the size and composition of the model's training data.
Team leaders can use Shilo to review conversations, monitor coaching, and identify training opportunities across agents. Post-call analytics and grading are positioned as ways to understand conversation quality and improve agent performance, though buyers should confirm the exact dashboard filters, exports, reporting depth, and permissions available in their package.
Shilo positions itself as enhancing the tools real estate teams already use, including CRMs, transaction management systems, and lead sources. The product can enrich CRM records with insights and next steps, but prospective buyers should verify current integration support for their specific CRM, phone system, and workflow during the evaluation process.
Custom quote only; Shilo does not publish an exact monthly price, annual price, or per-seat rate
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The currently available website messaging emphasizes Shilo's positioning as an AI assistant for high-performing real estate teams, with coaching, training, and assistant capabilities grouped as the core product areas. The site also promotes an announced $2.6 million seed round and states that Shilo is trusted to create impact by 100+ teams. Public proof points highlighted on the site include customer-reported operational improvements, but these results should be treated as vendor-published case study claims rather than independently audited benchmarks.
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