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Noseberry Digitals
AI for real estate

Real estate AI solutions. Agents, RAG, valuation, fraud, listings

Custom AI for real estate operators, brokerages, and PropTech founders. Lead qualification agents, RAG-powered tenant chat, AI listing generation, AVM, fraud detection, owner reporting copilots. Owned by you, model-portable, cost-controlled.

GPT-4o, Claude 3.5, Gemini 1.5, Llama · Multi-model · No vendor lock

Trusted by 50+ operators, PropTech companies & digital-first brands

HDFC Life
Axis Bank
Niva Bupa
Apollo Munich
Lufthansa
Amway
Kent
Harrington Housing
Hive Coliv
Edge Living
CDA Coliving
Fllat
Volley
TheVibes
CasaPay
JumboTiger
Everything Coliving
Bookmycoliving
Bhutani
Gulshan
CRC
M3M
Godrej
Omaxe
Sikka
Lodha
Mahagun
Prestige
Sawasdee
Who it’s for

Built for these operators

  • Coliving / BTR operators

    Multi-language tenant chat 24/7.

  • Real estate developers

    Automating channel-partner lead qualification at scale.

  • PropTech founders

    Shipping AI MVPs in 60–90 days.

  • Brokerages

    Automating listing copy + photo classification.

  • Property managers

    AI maintenance triage + owner reporting.

  • Investment platforms

    AI deal-screen agents.

What’s included

Everything you need, in one engagement

  • AI lead qualification agents

    Qualify, route, book site visits via WhatsApp + email + CRM.

  • RAG-powered tenant + buyer chat

    Grounded in inventory, FAQs, policies, multi-language.

  • AI listing generation + classification

    Copy, photo tagging, amenity extraction.

  • AI valuation + comparables

    Custom AVM or wrappers around ATTOM / CoreLogic.

  • Fraud + risk detection

    Booking fraud, payment fraud, identity verification.

  • AI owner / investor reporting

    Auto-generated reports, copilots for portfolio queries.

  • Document intelligence

    Lease parsing, contract review, KYC document checks.

  • Search intelligence

    Semantic search over inventory, neighborhood guides, market reports.

How we work

A predictable, weekly cadence

  1. 01

    Discovery (Week 1)

    Highest-value AI use cases against funnel + ops cost.

  2. 02

    Data audit (Week 2)

    Data quality, integration surface, privacy constraints.

  3. 03

    Prototype (Weeks 3–8)

    Working prototype on real data, accuracy bar.

  4. 04

    Production build (Weeks 9–14)

    CRM/CMS/payment integration, observability, cost guardrails.

  5. 05

    Eval + tuning (Weeks 15–16)

    Eval suite, A/B framework, human-in-loop tuning.

  6. 06

    Operate (ongoing)

    Monitoring, prompt updates, model swaps, quarterly reviews.

Tech & methodology

Opinionated for real estate

  • Foundation models

    • OpenAI GPT-4o / GPT-4
    • Anthropic Claude 3.5
    • Google Gemini 1.5
    • Open-weight (Llama 3.1, Mistral)
  • RAG + embeddings

    • pgvector + Postgres
    • Pinecone / Weaviate
    • OpenAI / Voyage embeddings
  • Agents + orchestration

    • LangGraph
    • Vercel AI SDK
    • OpenAI Assistants
    • Custom state machines
  • Observability + evals

    • LangSmith
    • Helicone
    • Langfuse
    • Custom eval harnesses
  • Compliance

    • GDPR
    • SOC2
    • EU/India data residency
    • Encrypted at rest + in transit
Selected work

Real engagements, real outcomes

  • Case study

    Coliving WhatsApp lead agent

    Multi-language qualification + booking.

    • +40% qualified leads
    • 0 SDR headcount growth
  • Case study

    Multi-country developer RAG

    Tier-2 partner FAQ in 4 languages.

    • 65% deflection rate
  • Case study

    Brokerage listing AI

    Copy + photo tagging at scale.

    • 4–8 hours saved per listing
Outcomes

What clients walk away with

  1. 6–8 weeks

    to working prototype on real data

  2. +40%

    qualified leads (coliving lead-qual agent)

  3. 65%

    deflection rate (multi-language RAG support)

  4. Guardrails

    per-tenant + per-route cost guardrails baked in

Pricing

Pick the tier that fits

  • AI Prototype

    6–8 weeks

    • One use case
    • Working prototype on real data
    • Accuracy bar + eval suite
    Scope a prototype
  • Most popular

    AI Platform

    10–14 weeks

    • 2–3 use cases
    • Production observability
    • Cost guardrails baked in
    Scope an AI platform
  • AI Operating System

    16+ weeks

    • Custom fine-tuned models
    • Multi-agent orchestration
    • Embedded ops + tuning
    Plan AI OS
How we compare

Side-by-side, with the alternatives

  • Real estate domain

    Noseberry
    100+ ops
    Generic AI agency
    In-house build
    Hire-dependent
    Off-the-shelf SaaS (EliseAI etc.)
    Niche
  • Code + model ownership

    Noseberry
    100%
    Generic AI agency
    Varies
    In-house build
    Off-the-shelf SaaS (EliseAI etc.)
    Lock-in
  • Time to first prototype

    Noseberry
    6–8 weeks
    Generic AI agency
    10–16 weeks
    In-house build
    16+ weeks
    Off-the-shelf SaaS (EliseAI etc.)
    Days, limited fit
  • Production observability

    Noseberry
    Built in
    Generic AI agency
    Add-on
    In-house build
    Custom
    Off-the-shelf SaaS (EliseAI etc.)
    Black-box
  • Cost guardrails

    Noseberry
    Per-tenant + per-route
    Generic AI agency
    Varies
    In-house build
    Varies
    Off-the-shelf SaaS (EliseAI etc.)
    Per-seat
  • Data residency control

    Noseberry
    Your cloud
    Generic AI agency
    Varies
    In-house build
    Off-the-shelf SaaS (EliseAI etc.)
    Vendor
FAQ

Frequently asked questions

Which models do you build on?

OpenAI (GPT-4o), Anthropic (Claude 3.5), Google (Gemini 1.5), open-weight (Llama 3.1, Mistral) where data residency demands. Model-portable agents.

Do we own the prompts and the model?

Prompts, eval suites, agent code, fine-tuned weights. Yours. Closed-source foundation models stay with provider; we set up your direct billing.

How fast can you ship a prototype?

6–8 weeks for single use-case prototype with real data.

What if our data isn't ready?

We gate the work. Discovery flags risks, scope a 4-week data prep sprint if needed.

How do you control costs?

Per-route + per-tenant cost guardrails from day one. Streaming, prompt caching, model fallback (GPT-4o → 3.5 → Haiku).

Ready when you are

Model-portable 100+ real estate operators?

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