What is the Mae synth human AI from Reliant? Mae is a hyper-realistic, enterprise-grade synth human AI persona built by Minnesota-based Reliant AI specifically for the real estate industry, and as of May 13, 2026, she is now the consumer-facing AI on HomeServices of America brokerage websites. Mae can hold full client conversations, change appearance and voice by market, and liaison with human agents on what each buyer or seller is looking for. While Mae's first deployment is residential, the technology raises immediate questions for commercial brokers, leasing teams, and any CRE firm building a client-facing AI strategy. For comprehensive coverage of how AI is reshaping the industry, see our guide on AI commercial real estate.
Key Takeaways
- Reliant AI's Mae is the first hyper-realistic synth human AI persona deployed at scale by a major real estate brokerage, debuting at HomeServices of America on May 13, 2026.
- Mae can hold multi-turn conversations with consumers, change appearance and voice by market, and route qualified leads back to human agents with structured client intent data.
- For CRE brokers, the implications include first-touch tenant rep workflows, leasing inquiry triage, capital markets investor portals, and after-hours client engagement.
- Synth human personas raise immediate trust, disclosure, and compliance questions that CRE firms must address before deploying client-facing AI.
- The competitive gap is widening between firms experimenting with AI agents and those still relying on email and form fills as primary client capture.
What Mae Actually Does
HomeServices of America CEO Chris Kelly described Mae as a "Synth Human" capable of hyper-realistic interactions designed to make clients feel they are talking with a knowledgeable agent rather than a chatbot. According to Reliant AI, Mae is built on a multimodal foundation that combines large language model reasoning, voice synthesis, and avatar rendering. The product is designed for two-way deployment: Mae engages consumers directly and also briefs human agents with a structured summary of what the consumer is looking for, such as price range, geography, timeline, and qualification status.
The capability that distinguishes Mae from earlier conversational AI tools is multi-persona deployment. Kelly stated the company is developing different appearances and voice profiles so that the same underlying AI can present as a market-appropriate persona in Minnesota versus Florida versus California. This is a notable shift from generic chatbots toward branded, market-specific AI representatives. The voice and avatar layer leans on advances from foundation models including OpenAI's GPT Realtime 2, ElevenLabs voice models, and Synthesia-style video generation. As JLL and other major brokerage groups have noted, the proptech category is moving rapidly from experimentation to production-grade deployment.
Why This Matters for Commercial Real Estate
HomeServices is residential, but the workflow problems Mae solves are nearly identical to those CRE brokers face every day. Consider the typical commercial leasing inquiry: a tenant rep broker receives 30 to 50 inbound emails per week from prospective tenants, most of which require basic qualification, building tour scheduling, and document delivery. Mae-class agents can handle that first-touch layer at scale, freeing senior brokers to focus on the 10 percent of inbound activity that justifies their time.
The same pattern applies in capital markets and investor relations. A CRE sponsor running a $50 million multifamily offering may receive 200 to 400 inquiries from registered limited partners. Many of those inquiries are simple status questions or document requests. A synth human persona, configured with deal-specific knowledge and compliance guardrails, could handle the first 30 minutes of every conversation, escalating only when an investor signals serious intent. CRE investors looking for hands-on AI implementation support can reach out to Avi Hacker, J.D. at The AI Consulting Network for a workflow audit and persona strategy.
The Five CRE Use Cases That Open Up Today
- Leasing inquiry triage: Synth human personas can handle initial outreach from prospective tenants, gather space and timing requirements, and schedule tours, freeing leasing directors and tenant rep brokers to focus on closing.
- Investor relations: AI personas configured with PPM and offering memorandum knowledge can answer common LP questions about IRR targets, hold periods, NOI assumptions, and DSCR coverage on debt-financed deals.
- Property management front desk: For Class A office and multifamily, synth human personas can handle tenant requests, maintenance ticket intake, and visitor check-in during off hours.
- Capital markets first call: Investment sales teams can route initial inquiries to a synth human that qualifies the buyer's check size, asset type focus, and capital stack constraints before booking a call with the principal broker.
- Property tour pre-qualification: Listing brokers can deploy a persona that walks prospective buyers through high-level financials and market positioning, gating tour bookings to qualified inquiries.
The Trust and Disclosure Problem
The risk of a hyper-realistic synth human is that consumers may not immediately know they are talking to AI. Colorado's recently passed SB 26-189 on AI disclosure, along with similar bills moving through California and New York legislatures, will likely require explicit identification of AI agents in commercial transactions. Real estate firms deploying Mae-class technology need to bake disclosure language into the persona's opening statement and ensure compliance with state-by-state requirements.
Reliant AI claims Mae includes opt-in transcripting, identity badges, and human handoff triggers. CRE firms evaluating similar products should ask for the same controls plus an audit log of every conversation, the ability to review and override AI outputs before they reach clients in high-stakes negotiations, and clear documentation of what training data the AI is exposed to. If you are ready to transform your client-facing workflow with AI, The AI Consulting Network specializes in exactly this kind of guardrail design.
How the Economics Work
Reliant AI has not published full pricing, but industry comparables suggest enterprise synth human deployments run $50,000 to $200,000 per year for a multi-persona configuration, plus per-conversation costs. For a mid-size CRE brokerage handling 5,000 inbound inquiries per month, the unit economics typically pencil out when the AI can deflect 60 to 75 percent of first-touch volume that would otherwise consume broker assistant time at roughly $35 per hour fully loaded.
The math gets stronger when you factor in conversion rate improvements. CBRE and other major brokerage research groups have documented that response time is the single largest predictor of conversion on commercial leasing inquiries. A synth human persona responding in under 30 seconds, 24 hours a day, can double or triple conversion rates compared to human responses delayed by hours or overnight. The CRE sales volume forecast to increase 15 to 20 percent in 2026 also means brokers are operationally stretched, making AI triage more valuable.
Where the Technology Is Headed Next
Mae is an early production deployment, not the end state. Expect three trajectories over the next 12 months. First, video-native synth humans that can join Zoom or Teams meetings and present like a colleague. Second, deeper CRM integration so the persona has live access to deal pipeline data, lease abstracts, and rent roll information. Third, voice-first deployment through phone systems, allowing the synth human to handle inbound calls to a broker's published line. The market context is clear: 92 percent of corporate occupiers have initiated AI programs, and AI in real estate is projected to reach $1.3 trillion by 2030 at a 33.9 percent CAGR. CRE firms that wait will find themselves competing against firms that have already retooled.
Frequently Asked Questions
Q: Is Mae a chatbot or something different?
A: Mae is materially different from a traditional chatbot. She combines large language model reasoning, voice synthesis, and avatar rendering into a single multimodal AI persona designed to feel like a knowledgeable human agent. Traditional chatbots handle scripted Q and A; Mae handles open-ended conversation and routes structured intent data back to human agents.
Q: Can CRE brokers actually use Mae today?
A: Reliant AI's initial enterprise rollout is focused on residential brokerages through HomeServices of America, but the technology is brokerage-agnostic. Commercial brokerages can either license from Reliant or build comparable systems by combining foundation models like Claude Opus 4.7, GPT-5.5, or Gemini 3.1 Ultra with voice and avatar layers from ElevenLabs and Synthesia. Implementation typically takes 60 to 120 days for a production deployment.
Q: What disclosure rules apply to AI personas in commercial real estate transactions?
A: As of May 2026, Colorado's SB 26-189 requires AI disclosure in covered transactions, and similar bills are advancing in California, New York, and Illinois. At the federal level, the FTC has signaled enforcement attention on undisclosed AI use in consumer-facing commerce. CRE firms should disclose AI use at the start of every conversation, retain transcripts for at least seven years, and provide a clear escalation path to a human licensed broker.
Q: Does deploying a synth human persona expose a brokerage to fair housing or fiduciary risk?
A: Yes, potentially. Brokerages remain responsible for the conduct of any agent acting on their behalf, including AI agents. Firms should audit persona outputs for fair housing compliance, ensure the AI cannot make promises beyond authorized scope, and require human review for any communication that touches negotiation, valuation, or fiduciary advice.
Q: How should a mid-size CRE brokerage start with this technology?
A: Start narrow. Deploy a synth human persona for one workflow, such as after-hours leasing inquiry triage, and measure conversion rate, response time, and broker hours saved over 60 to 90 days. Expand to additional workflows only after the first deployment is proven and compliance guardrails are validated. For personalized guidance on implementing these strategies, connect with The AI Consulting Network.