AI consultants for commercial real estate brokerages

King & Company wrote this page, and King & Company is one of the firms on it. We build AI workflows for brokerage teams, so we have an interest in how you read what follows, and you should weigh it with that in mind. People search for the best AI consultants for commercial real estate, and there is no single answer to that search. The right choice depends on the kind of help your team needs, so this page describes the kinds, lists real providers of each in alphabetical order, and spends most of its effort on the questions worth asking any of them.

The four kinds of help available

A team lead in leasing, capital markets, or property management usually has four places to turn. They solve different problems, and many teams use more than one.

Type of provider	What you get	Fits when	What to check
CRE software product	A subscription to a tool built for a specific brokerage job	The job is common across brokerages and the tool's way of doing it is close to yours	Where your documents are stored and what you can export if you leave
Large consultancy	Strategy, operating model, and transformation work at the firm level	The decision belongs to firm leadership and spans finance, operations, and technology	Who staffs the work day to day and what is delivered at the end
In-house platform at a large brokerage	AI tools your own firm built and approved for its data	You work at a firm that has one and the task is covered by it	What the platform covers for your team's specific work and what it does not
Custom workflow builder	Workflows, skills, or software built around how your team works	The value is in your team's own templates, review habits, and systems	Who does the building, who owns the result, and how the team is trained

CRE software products

These are products you log into. A vendor has chosen a brokerage job, built a tool for it, and sells access. The advantage is speed, because the tool exists today. The trade is that the product does the job the vendor's way, and your documents may be stored in the vendor's system, which is worth asking about.

Large consultancies

The large firms work at the level of the whole company, and some publish research on the subject. A Deloitte article on generative AI in commercial real estate, published in December 2023, lays out four ways a real estate firm can adopt the technology (use existing applications, integrate third-party APIs, deploy open-source models, or build private language models) and says there may be trade-offs in choosing one approach over another, including cost and data privacy. We find that framing helpful to have in mind before any sales conversation.

In-house platforms at the big brokerages

Some of the largest brokerages have built AI platforms of their own. JLL introduced JLL GPT in August 2023 and announced its JLL Falcon platform in October 2024, and its AI page says every JLL team a client works with is powered by Falcon. CBRE says it introduced Ellis AI in early 2023, and its AI page describes sales, research, valuation, and lease administration teams using it. Each firm describes its platform as a tool for its own teams and clients, so neither appears in the list below. They matter here because, for a team inside one of those firms, the first question is what the firm platform already does, and the second is what remains that is particular to the team.

Firms that build custom workflows inside a team

These firms build around the way a specific team works. Some build software, some build agents on top of a firm's data, and some embed a person with the team, which is the model often called forward deployed engineering. The result should fit your templates and your review process. The trade is that it asks for your team's time during the build, and the result depends on the individual doing the work.

Providers a brokerage team might consider

The list is alphabetical (ignoring a leading "The") and is not a ranking. Each description uses only what the firm states on its own website, which we opened on October 2, 2026. We make no judgment here about the quality of any of them.

The AI Consulting Network

The AI Consulting Network says it installs production AI workflows into commercial real estate teams, and it names underwriting automation, investor reporting, lease abstraction, due diligence, deal analysis, and property management. Its site says it serves CRE investors, multifamily operators, syndicators, brokers, and property managers. Type: custom workflow builder.

Ascendix

Ascendix describes itself as an AI and real estate software development company, and it lists a corporate office in Dallas, Texas. Its site offers custom software development, proptech consulting, and its own real estate software products, and its AI services include custom AI development, AI document processing, and AI chatbots. The client types it names are real estate brokers, commercial real estate firms, owners and operators, and proptech startups. Type: custom software builder.

Buildout

Buildout describes itself as a connected software platform built for commercial real estate brokerages, combining CRM, marketing, data, and back-office automation. Its site says the platform is designed for brokerages of all sizes, from boutique firms to national teams, and that it uses AI for tasks such as generating proposals and marketing materials and writing property descriptions and outreach emails. Type: software product.

Deloitte

Deloitte's real estate practice lists real estate managers, brokers, and advisers among the segments it serves, alongside REITs, real estate funds, homebuilders and developers, proptech companies, and tenants and occupiers. The capabilities on that page include operations transformation, finance transformation, real estate strategy, audit and assurance, and tax. Its Center for Financial Services publishes research on generative AI in commercial real estate, including the article linked above. Type: large consultancy.

Henry

Henry describes its product as AI built for CRE teams. Its site says it automates underwriting, pitch decks, and comps research, producing underwriting models in Excel, pitch decks in a firm's brand, market research with cited sources, and buyer lists drawn from firm data. Type: software product.

King & Company

King & Company is a forward deployed engineering firm, and it is the author of this page. It embeds with a brokerage team across leasing, capital markets, or property management and builds AI workflows, Claude skills, and integrations between the systems the team already runs, with lease abstraction, a first pass at a broker opinion of value, and survey workbooks as examples. The person who scopes the work is the person who builds it, the team is trained during the build, and the client owns everything that is built. Its two partners live in Boston and Miami, and it has clients in Atlanta, Memphis, Boston, and the Miami and Orlando area. Type: custom workflow builder.

Pacific Software Ventures

Pacific Software Ventures describes itself as a San Francisco based team building AI for commercial real estate. Its services include AI consulting, an intelligence layer it calls a Company Brain with custom AI agents built on top, AI training through its CRE AI Institute, and custom projects. Its site addresses investors and asset managers, brokers and advisors, and portfolio operators. Type: custom workflow builder.

Prophia

Prophia offers AI-powered lease abstraction for commercial real estate and lists a San Francisco address. Its site describes turning the documents that govern a business into verified intelligence, and it addresses leasing teams, acquisitions teams, property managers, and investors. Type: software product.

How to choose: five questions for any firm

These questions apply equally to every provider above, King & Company included. A good provider will answer each of them in plain terms on the first call.

Who does the building?

Ask for the name of the person who will do the work and how much commercial real estate they have seen. At some firms the person who sells and scopes the work is different from the person who builds it, and the builder learns your business secondhand. That can work, but you should know it going in. Ask whether the builder will see real documents (an actual lease, an actual offering memorandum, your actual survey template) or a description of them. In our experience, work built against real documents holds up better on the next deal. For a software product, the equivalent question is how much of the setup is done for you and how much falls to your team.

Where does the data live?

Leases, rent rolls, client lists, and deal terms are confidential, and some are covered by agreements your firm signed with clients. Ask exactly where a document goes when someone on your team uploads it. The possibilities are your own AI workspace under your firm's account, the vendor's cloud, or a consultant's laptop, and they carry different obligations. Ask whether your documents are used to train anyone's models, who at the provider can see them, how long they are retained, and what happens to them when the contract ends. If you work inside a large brokerage, ask your own technology group what is permitted before you ask any outside firm. Get the answers in writing, in the contract or the NDA, and not only in the sales conversation.

Who owns the result?

With a software product you own your data and rent the tool, so ask what you can export and in what format. With custom work, ask whether the prompts, skills, templates, code, and documentation are yours outright, and whether they will run without the builder's proprietary platform or an ongoing fee. A simple test is to ask what you would still have, and what would still work, a year after the last invoice. Also ask whether the provider can reuse what it built for you with another brokerage in your market, and decide whether that matters to you.

How does the team get trained?

A workflow nobody uses is an expense. Ask how training happens and who receives it. A recorded webinar and a user guide are one answer. Sitting with the analyst who owns the lease abstracts while she runs her own documents through the new process is another. Ask what a broker or coordinator will be able to do alone at the end, and how the provider will know. Ask what happens when a new hire joins six months later. The broader point is that the review step, where a person checks what the AI produced before it goes to a client, has to be taught along with the tool, because the team member's name is on the work product.

What happens after the engagement?

Models change, templates change, and your team's process changes. Ask who maintains what was built, what that costs, and whether your own people can make routine changes without calling anyone. Ask what the handover includes: documentation, a list of what was built, and a plan for what to build next are reasonable things to expect. For a product, ask about contract length, price changes at renewal, and how you leave. For a consultancy, ask whether the engagement ends in recommendations or in working systems, and who implements the recommendations if it is the former.

Matching the type to the need

A few rules of thumb follow from the above. If the need is a common task done at volume and a product already does it close to the way you would, buy the product and spend your effort on the data questions. If the need is a firm-wide decision about operating model, budget, and governance, that is the work a large consultancy is organized to do. If you sit inside a brokerage with its own platform, learn that platform first. If the need is specific to how your team prospects, prices, abstracts, or reports, and your templates and systems are part of the value, look at firms that build inside the team, and hold them to the five questions above.

Much of this work can happen inside shared workspaces and on calls, though some teams prefer a firm that can be in the room. We have written separate pages on AI consulting firms in Boston, Atlanta, and the Miami and Orlando area for readers who want that view.

Common questions

Who wrote this comparison, and is it independent?

King & Company wrote it, and King & Company is one of the firms on the list. The other entries are described only with facts each firm publishes on its own website, and the list is in alphabetical order with no ranking.

Should a brokerage team buy a CRE AI product or hire a firm to build something custom?

A product fits when the job is common across brokerages and the vendor's way of doing it is close to yours, such as generating marketing materials or abstracting leases. Custom work fits when the value is in how your particular team does the job, with its own templates, review habits, and systems. Many teams end up using both.

We work at a large brokerage that already has its own AI platform. Do we still need outside help?

Start with what your firm already provides, because it is approved for your data and connected to firm systems. Outside help is worth considering for the work that is specific to your team and that the firm platform does not cover, and any outside firm should work within your company's technology and data policies.

What should a brokerage ask an AI firm before signing?

Ask who does the building, where your documents and deal data will live, who owns what gets built, how your team will be trained, and what happens when the engagement ends. The answers tell you more than a demo does, and the same five questions apply to every provider on this page.

Where is King & Company based, and where are its clients?

King & Company's two partners live in Boston and Miami. The firm has clients in Atlanta, Memphis, Boston, and the Miami and Orlando area.