Best AI Tools for Mortgage Brokers in 2026

Bulma is the best AI tool for mortgage brokers. Bulma gives you quick access to policies from 52+ lenders and helps you work through client scenarios, from finding suitable lenders to comparing borrowing power. Each policy answer includes the lender’s wording, while scenario results show which lenders fit, what conditions apply and which documents you’ll need.

Other AI tools can be useful for specific jobs, such as comparing rates, preparing documents or drafting emails. But some are more expensive with tighter usage limits, some aren’t fully independent of lenders or aggregators, and others aren’t as accurate as Bulma. Here are the best AI tools for mortgage brokers and what each one is useful for.

Top AI Tools for Mortgage Brokers in 2026

1. Bulma

Bulma is an AI assistant for Australian mortgage brokers that handles lender policy research and scenario planning across 52+ lenders and about 50 policy areas. Its coverage runs from the big four banks and Macquarie to customer-owned banks and specialist non-banks such as Pepper Money, Liberty and La Trobe Financial. You can ask in plain English using broker shorthand, and follow-up questions keep the conversation’s context.

Bulma’s Scenario Planner takes your client’s whole scenario once, typed in or filled from uploaded payslips, a fact find or your customer relationship management (CRM) system. It then groups the lenders by whether the scenario fits standard policy, fits with conditions or needs an exception, and lists each lender’s conditions and documents. It also works out borrowing power at each lender from that lender’s own servicing inputs, and shows known exception pathways with a confidence level.

Each answer quotes the lender’s policy wording and shows the lender, the policy area and the date Bulma last updated that policy. A comparison checks every covered lender and names those whose policy doesn’t address the point. Bulma refreshes lender policies as lenders publish changes and alerts you when a policy you’ve asked about changes.

Bulma ranks first for the broker who needs a defensible residential lender shortlist. For a file with complex income, Scenario Planner identifies which covered lenders fit, calculates borrowing power at each and lists the conditions and documents to check. The quoted policy shows why each lender appears, while confidence-labelled exception pathways point to cases that need a lender conversation.

The lender sets the final borrowing figure. Rates, fees and lodgement remain separate jobs.

Bulma charges per plan: Solo covers one broker, and Team includes five members with extra members at a per-seat fee. Every plan includes generous usage limits for policy and scenario questions, and the 14-day trial needs no credit card. Bulma’s Policy Advisor and Scenario Planner cover the policy and scenario work described above.

2. CreditPolicy

CreditPolicy puts policy research, servicing and document drafting in one workspace. Its panel covers 96 lending brands across residential, commercial, asset finance and personal lending. Policy Chat gives page-cited answers.

Residential Servicing compares lender servicing from one set of inputs, and Client AI turns your notes into a client profile. Form Fill reuses that reviewed data in lender forms, and AI Document Studio drafts broker-branded proposals. You can also ask questions by email, or connect an outside AI assistant through Model Context Protocol (MCP).

CreditPolicy is the better fit when you need lender forms and branded proposals prepared beside policy answers. Its 96-brand panel spans residential, commercial, asset finance and personal lending, so that total is not a count of comparable residential lenders. Bulma leads for the residential broker who needs policy fit and borrowing power from one scenario, with quoted wording and confidence-labelled exception pathways.

CreditPolicy sells a Solo plan for one broker and a Team plan priced per seat, with at least three seats. Each seat draws on a monthly allowance of 1,500 credits. Both plans start with a 7-day free trial that asks for a card at the last step.

CreditPolicy’s privacy policy says client and deal records are hosted in Sydney, while OpenAI generates answers in the United States and Google analyses documents. The policy says its AI providers’ terms stop them training general models on that content. Through MCP, a connected assistant can read the policy library and read and write your client records, and anything returned sits under that assistant’s own terms.

3. Quickli

Quickli is a servicing calculator first, running serviceability across 51 or more lenders from one set of inputs. Serviceability is whether your client can afford the loan under each lender’s own calculation. The Pro plan adds the AI features.

Jiffi AI answers policy questions from full lender policy documents that Quickli checks weekly, and it can compare rates and fees. Quickli says Jiffi also draws on its own knowledge from broker experience and business development manager (BDM) insights. Confirm any point that matters against the written policy, because that knowledge isn’t the lender’s rule.

Doc Handler renames uploaded client documents, extracts their details and fills the scenario. Loan Notes drafts submission notes, and Pro also adds a self-managed super fund (SMSF) servicing tool.

Quickli is third because Jiffi AI needs Pro and shares 3,200 monthly credits per person with loan submission notes. Quickli is a better fit when its 51+ lender calculator, rates and fees or lender-calculator exports are required. Bulma keeps policy fit and borrowing power together for the 52+ residential lenders it covers.

Quickli sells Core and Pro plans for a single user, and per-seat Core and Pro plans for teams. Administrator and view-only users are free, and every plan starts with a 21-day free trial.

Quickli’s trust centre lists certification to ISO/IEC 27001, the international information security standard, and Sydney hosting for core services. It says its AI providers keep no customer data and don’t train on it, though some AI processing happens offshore.

4. Thryvve

Thryvve is a policy assistant with unlimited questions and every feature on every plan. It answers from official lender policy documents across about 30 lenders, and each answer points to its source.

Thryvve compares lenders side by side, scans your panel for possible matches and alerts you when a lender changes a policy. It also analyses self-employed or fly-in fly-out (FIFO) payslips and checks an application against lender conditions before you lodge it. Email drafts and best interests duty (BID) documentation round out the paperwork help.

Thryvve sits fourth because it helps with policy questions and file drafting, while Bulma also calculates borrowing power from the same residential scenario and ranks lenders by policy fit. Thryvve is a useful choice when unlimited questions and its payslip or drafting tools decide the job. Its roughly 30-lender policy library is narrower than Bulma’s coverage of 52+ residential lenders.

Thryvve charges per seat and bills monthly or yearly. The 30-day free trial needs no payment method.

Thryvve’s frequently asked questions (FAQ) page says it doesn’t keep your client’s personal information beyond your session. Its privacy policy keeps core account data on Australian servers and commits to telling the Office of the Australian Information Commissioner (OAIC) within 72 hours of a serious breach.

5. Cynario

Cynario pairs a policy assistant, Charli, with a marketing assistant, Alex. Charli assesses a scenario against about 40 residential lenders, covering loan-to-value ratio (LVR), income type, entity structure, security, postcode and documentation pathway.

You can ask Charli in chat, or email it a question without signing up. It also runs inside a client record in the Salestrekker 2.0 CRM system. Cynario says Charli answers from lender data alone, cites the policy wording behind each answer and doesn’t browse the web.

Cynario says every 40 policy questions earn one continuing professional development (CPD) point, tracked in the platform. Alex writes and publishes social posts, client emails and blog articles, while Cynario Reviews turns client feedback into posts.

Cynario ranks fifth because its added tools focus on marketing, while the higher-ranked specialist choices do more of the loan file’s policy and scenario work. It suits a broker who wants policy research and marketing help in one subscription.

Every Cynario plan includes unlimited archived conversations, and the 21-day free trial needs no credit card. Cynario’s terms let the subscriber set each user’s access, and its site offers optional multi-factor authentication (MFA).

Cynario’s privacy policy says its storage providers may process data in the United States. Match that location to the client-data rules your brokerage follows.

6. ChatGPT Business

ChatGPT Business is a general assistant for writing and analysis from material you give it, such as a policy passage you’ve already checked. It can rewrite a client email in plain English, summarise a long document or draft a file note.

ChatGPT works from its training, web search and the apps you connect, such as Google Workspace, Slack or Microsoft 365. OpenAI lists no lender policy library, so check every lender rule it writes against that lender’s own policy.

ChatGPT Business is sixth because it starts from general sources, while the five tools above start from lender policy. Drafting is where it helps most, and its workspace agents run customised workflows across the apps you connect.

OpenAI prices the Standard seat per user, billed monthly or yearly, for teams of two or more. Business data isn’t used for training by default, and the workspace supports single sign-on (SSO) and MFA.

Chats stay until someone deletes them, and OpenAI then removes them from its systems within 30 days. Custom retention rules are an Enterprise feature.

7. Microsoft 365 Copilot Business

Microsoft 365 Copilot Business is an add-on that brings AI into Word, Excel, PowerPoint, Outlook and Teams. You buy it on top of an eligible Microsoft 365 Business plan.

Copilot searches your emails and files through the same permissions your staff already have. Before rollout, check who can open which client folders, since Copilot applies those permissions as they stand. Its pre-built agents, such as Researcher and Analyst, handle research and data analysis across that content.

Copilot comes last because only brokerages already on an eligible Microsoft 365 Business plan can add it. Microsoft lists no lender policy content, so Copilot is for drafting and searching your own files.

Microsoft prices Copilot Business per user, paid monthly or yearly. Under Microsoft’s enterprise data protection terms, nothing you type into Copilot or get back from it is used to train Microsoft’s foundation models. The same applies to content it reaches through Microsoft Graph, the service that connects it to your files and email.

Research, Drafting and Automation

A specialist policy tool answers from a library of lender policy that its vendor maintains. A general assistant works from its training, web search and the files or apps you connect, and neither general assistant here documents a lender policy library.

That difference changes what you check. With a specialist tool you confirm each condition in the lender policy it came from, while a general assistant’s lender rules all need checking from scratch.

Try both with one fictional client. She’s a casual aged-care worker with nine months at her current employer and three years in aged care, earning $78,000 a year as a pay as you go (PAYG) employee. She repays a car loan at $420 a month and has a 10% deposit for a home she’ll live in.

Ask a specialist tool which lenders accept her casual income, then confirm each condition it lists in that lender’s policy. Put the same question to a general assistant and compare each lender rule it states with that lender’s policy. The guide to how lenders assess casual income covers the conditions you’ll be checking.

Once the passages are checked, a general assistant can write the file note from them. It can also draft the questions you’ll send the lender’s BDM.

An AI agent for mortgage brokers keeps going after the first result: it might read a payslip, fill a form and save the file without being asked again. An answer tool stops once it has returned one answer or draft.

On this list, CreditPolicy’s Form Fill fills lender forms from reviewed client data, and Quickli’s Doc Handler fills a scenario from uploaded documents. In Bulma, uploaded payslips or a fact find fill the Scenario Planner, which then checks the scenario against each covered lender’s policy. Copilot Business and ChatGPT Business add agents that search, analyse or run workflows across your connected content.

Agents need tighter controls than answer tools, because they can change records as well as read them. Decide which records each agent may touch and which staff member answers for it. Then set it to pause for a person’s approval before it saves anything to your client’s file or sends a message.

Give any AI automation a written stop rule that says who can pause a run and what happens to a half-finished record. Keep a log of each step, so you can find where a run went wrong and redo that step by hand.

When you upload a payslip, bank statement or identity document, AI mortgage document processing reads it and fills the matching fields in your scenario. From a payslip it might capture the employer, pay period, gross pay and year-to-date (YTD) income. A bank statement gives it the balance and regular repayments.

Match every captured field to the page it came from before you use it. Look closely at pay frequency, at whether YTD income fits the pay rate and at overtime or allowances the lender treats differently. On statements, watch for repayments to debts your client didn’t mention.

A captured name and licence number don’t complete verification of identity (VOI). Run your licensee’s VOI process for that step.

AI can also answer calls and book appointments for a brokerage. The guide to AI receptionists for mortgage brokers shows how to test call intake and the handover to a person.

Check a Worked Output

A worked output passes your check only when every statement in it matches a lender rule you’ve read yourself. The steps below use the fictional aged-care worker, and the answer shown is made up for this example.

1. Write the prompt with minimum data only, like this one: “Casual PAYG aged-care worker, nine months in current job, three years in the industry, $78,000 a year, buying a home to live in at 90% LVR. Which lenders accept casual income with under 12 months in the current job, and on what conditions?”
2. List each lender the answer names, with the condition and source it gives for that lender. In this made-up example, the answer says that Lender A accepts casual income after six months with any employer, with no LVR limit.
3. Open the source cited for Lender A and confirm it covers this product and a home your client will live in. Then check what else the source requires, such as a minimum time in the industry, a finished probation period or a lower maximum LVR.
4. Mark each claim as supported, unsupported or missing. Here the source says nothing about any employer or an unlimited LVR, so both claims come out.
5. Write down what the answer left out, such as the documents the lender wants as proof of casual income. Turn each condition the source leaves open into a question for the lender’s BDM.
6. Sign the corrected note with your name, the source and the date you checked it. Only then does it go into your client’s file.

Absolute words such as always, any or no limit mark a statement you can’t use until the source confirms it. So does a figure that’s missing from the cited source. A rule with no citation, or a citation to a different product, sends you back to the lender’s own policy.

Run every tool you’re trialling on the same fictional scenario. For each one, record what its answer left out, any claim its source doesn’t back and the check someone must make before the output joins a file.

Tool	Output to check	Omissions to look for	Unsupported claims to look for	Human check before file use
Bulma	Policy Advisor answer quoting the policy wording, or a Scenario Planner lender list with conditions and borrowing power	Lenders outside its coverage	A condition the quoted wording doesn’t contain, or an exception pathway treated as written policy	Read the quoted wording, confirm the product and loan purpose, and confirm any exception pathway with the lender or BDM
CreditPolicy	Policy Chat answer, servicing result, filled form or drafted proposal	Conditions missing from a drafted proposal	A drafted sentence with no citation	Compare every filled field and drafted claim with the file
Quickli	Servicing result, Jiffi AI answer and auto-filled scenario	Income or debts Doc Handler didn’t capture	A point from Quickli’s own knowledge shown as lender policy	Match each auto-filled figure to the payslip or statement
Thryvve	Market scan and single-lender policy breakdown	Lenders outside its library of about 30	A lender rule with no policy reference	Read the referenced source
Cynario	Charli scenario assessment	Lenders outside its residential panel	A condition missing from the cited policy wording	Read the cited wording and confirm each condition in the lender’s own policy
ChatGPT Business	Draft note from the passage you supplied	Conditions in the passage that the draft dropped	A rule that isn’t in your passage	Read the draft against the passage line by line
Microsoft 365 Copilot Business	Draft built from your Microsoft 365 files	Relevant files it skipped	Details pulled from another client’s file	Confirm the source files belong to this client and are the latest versions

Use the last column to decide which output a broker must verify before it enters a client file.

Choose a Tool You Can Operate

The right tool covers the research or admin job that takes most of your week and produces output your team can check on every file. A sourced policy answer needs one check against its source, while a filled form or drafted proposal needs checking field by field.

Tool	Price structure	Published data controls	Review effort	Main limit
Bulma	Per plan: Solo for one broker, or Team with five members and extra members per seat. Generous usage limits for policy and scenario questions	Privacy policy describes limited service-provider sharing	Read the quoted wording and confirm any exception pathway with the lender	Doesn’t quote rates or fees, or lodge applications
CreditPolicy	Solo plan, or Team per seat with three seats minimum. 1,500 credits a seat each month	Client records hosted in Sydney. AI providers barred from training on its content	Check every filled form and draft	Monthly credit allowance
Quickli	Core or Pro, for one user or per team seat. Pro adds 3,200 Jiffi and Loan Notes credits a person each month	ISO/IEC 27001. Sydney hosting. AI providers keep no data	Check auto-filled figures and each Jiffi point	AI features need Pro
Thryvve	Per seat, with unlimited questions and every feature on every plan	Client details not kept past the session	Read the referenced source	About 30 lenders
Cynario	Plans with unlimited archived conversations	Optional MFA. Data may be processed in the United States	Confirm each condition in the lender’s policy	Residential lenders only
ChatGPT Business	Per user, billed monthly or yearly, two users minimum	No training on business data by default. SSO and MFA	Read the draft against your source line by line	No lender policy library
Microsoft 365 Copilot Business	Per-user add-on, billed monthly or yearly	Excluded from foundation-model training. Copilot follows your permission, retention and audit settings	Check which files it used	Needs an eligible Microsoft 365 Business plan

Each tool here bills by plan or by seat, so count the seats you’d actually use. Then check which features need a higher plan and how far any credit allowance stretches across a normal month of files.

Five capabilities change what the tool produces and what the broker must check.

• Bulma’s Scenario Planner checks a whole scenario against each covered lender’s policy and works out borrowing power at each lender. An exception pathway it shows isn’t written policy, so check its confidence level and confirm it with the lender or their BDM. The lender’s own assessment sets the final borrowing figure.
• Quickli’s Doc Handler fills a scenario from uploaded documents, so it changes figures you’ll rely on. Check every field it fills.
• CreditPolicy’s MCP connection lets an outside assistant read the policy library and read and write client records. Anything it returns then sits in that assistant’s chat, under that provider’s terms.
• Copilot’s Researcher and Analyst agents search and analyse whatever content the signed-in person can open. Their reach is only as narrow as your permissions.
• ChatGPT Business workspace agents run customised workflows across the apps you connect. Review each workflow’s app access before you switch it on.

If most of your AI time goes on writing, a general assistant covers it. Either general assistant can turn checked policy text into a client email or file note, but neither tells you what a lender accepts. The comparison of Bulma and ChatGPT sets out where each fits, with Bulma handling the policy research and scenario planning.

Questions about what a lender accepts belong with a specialist policy tool. Bulma, CreditPolicy, Thryvve, Cynario and Quickli on its Pro plan all answer from lender policy, and Bulma also plans your client’s whole scenario across its 52+ lenders. To pick by the lenders you use and the other jobs you want covered, compare Bulma and CreditPolicy, Bulma and Quickli, Bulma and Thryvve or Bulma and Cynario.

Before you buy either kind, check what your aggregator already gives you. Your aggregator is the group whose software and lender panel you lodge through, and some aggregator platforms include a servicing calculator or policy search. Mortgage Choice, for example, has added AI policy search to its Lending Toolkit for its own brokers.

A second tool means another login and one more place your client’s data sits. For choices between systems that don’t use AI, see the guide to mortgage broker software.

Govern AI Use Across the Brokerage

Every AI output in your brokerage needs a named broker’s approval before it becomes part of a recommendation. Staff also need written limits on the jobs they may give an AI tool and the client details they may enter.

Approved Uses and Client Data

Allow two uses to start: researching lender policy and drafting from material a broker has already checked. Prompts carry only minimum-data scenarios, so names, birth dates, street addresses, bank account details and licence or passport numbers stay out.

Vendor Due Diligence

Before you approve a tool, check its current terms for retention, model-training use, AI subprocessors, staff permissions and incident support. Ask the vendor in writing about a control its published terms do not establish, and keep the answer with your approval record. The known controls below show why a privacy or security badge alone is not enough.

Vendor	Published data terms	Access or incident controls
Bulma	Privacy policy keeps data only as long as reasonably necessary and describes limited service-provider sharing	Team has five members, shared history and usage analytics
CreditPolicy	Client and deal records are removed within 90 days of closure. OpenAI and Google process AI work in the United States under no-training terms	Each user reaches only their own client and deal records. The policy says it tells you promptly about a client-data breach
Quickli	Jiffi history stays in the account. AI providers retain no customer data and training is off; Doc Handler files expire after 24 hours by default	Only the owner shares scenarios. Its incident process includes customer notice
Thryvve	Client details end with the session; core account details are kept for two years after closure	Each team member has their own login. Its privacy policy commits to notifying the OAIC within 72 hours of a serious breach
Cynario	Data may be processed in the United States and kept while the relationship or law requires it	The subscriber sets each user’s access
ChatGPT Business	Chats remain until deleted and are then removed within 30 days. Business data is not used for training by default	Role-based controls are listed for Enterprise. A security team is on call around the clock
Microsoft 365 Copilot Business	Microsoft 365 retention rules apply; prompts, outputs and Graph content are excluded from foundation-model training	Copilot follows Microsoft 365 permissions and sensitivity labels. A security team handles incidents

The Office of the Australian Information Commissioner’s guidance on commercially available AI products tells businesses to assess AI products before adoption. It also recommends against entering personal information into publicly available generative AI tools.

Staged Team Pilot

Run the pilot on fictional files so errors show up before any client is affected. Widen access only after the checks have held.

1. Pick two or three staff for the first round.
2. Build fictional files that range in difficulty, starting with a single-condition question and working up to the casual-income scenario above.
3. Write the correct answer and its lender source for each file before anyone runs it, so the team marks results against a known answer.
4. Meet each week to go through every wrong or incomplete answer and note which check caught it.
5. Add staff only when the checks have caught every error. If a tool can’t handle a task, take that task off the approved list and research it in the lender’s own policy.

Permissions by Role

Set permissions by role before anyone enters client details. The table suits a small brokerage, and a larger team can tighten it.

Permission	Broker	Processor	Credit staff	Administrator
Workspace access	Own and assigned clients	Files they’re assigned	Files sent for review	Adds and removes users, with no client files unless assigned
Client-data entry	Minimum-data scenarios	Documents for assigned files	Review notes only	None
Answer approval	Signs off output used in a recommendation	Prepares work for a broker to sign off	Checks citations and flags gaps	None
Prompt and export visibility	Own prompts and exports	Prompts on assigned files	Prompts on files under review	Usage and audit views where the tool has them
Offboarding	Access removed on the last day	Access removed on the last day	Access removed on the last day	Removes access and moves shared prompts to another user

Log every permission change with the date, the person who made it and the reason. Keep that record after staff leave, because it shows who could see a client’s scenario at any point.

Minimum-Data Scenario Template

A minimum-data scenario keeps the facts a policy question turns on and drops anything that points to a person. Build every prompt from these fields.

• Income type and amount, such as casual PAYG at $78,000 a year
• Time with the current employer and time in the industry
• Monthly repayments and card limits
• Deposit amount and where it came from
• Whether the property is a home or an investment, and its type
• The exact policy question

An unusual mix of details can point to one person even without a name. An aged-care worker in a town of 2,000 people on an exact salary might be the only person who fits. When the facts can’t be made anonymous, use your licensee’s approved route for client data, or research the lender’s policy without entering the scenario.

Governance Checklist and Risk Assessment

Use this table as the core of your AI governance checklist, and review it whenever you add a tool or a task. Each row pairs a risk with the control that addresses it and the person who owns that control.

Risk	Warning sign	Control	Owner
Client privacy	A client’s name or address appears in a prompt	Minimum-data template and a list of approved tools	Principal
Use outside the approved list	Staff use AI for a task nobody approved	Written list of approved uses, plus a pilot before adding a task	Principal
Wrong output	A lender rule with no source appears in a draft recommendation	A cited source and a named broker’s sign-off	Reviewing broker
No clear reviewer	A file reaches the client with nobody’s sign-off	One named reviewer for each file	Principal
Vendor terms change	A vendor changes its retention, training or subprocessor terms	Recheck vendor documents each quarter and keep written replies	Administrator
Incident	Client data is exposed or a tool fails partway through a task	Incident contact, containment steps and a data breach assessment	Principal and administrator

This checklist covers AI use only. For your wider obligations, work through the mortgage broker compliance checklist.

Lender Policy APIs and Integrations

Research can leave a policy tool by four routes. They are a published policy application programming interface (API), a vendor-built CRM link, a custom build and a person copying text across. Plan around a route only when the vendor’s documentation shows it on the plan you’d buy.

Route	What it is	Proof to ask for	On this shortlist
Published policy API	An interface other software calls, with set request and response fields, limits and error codes	Developer documentation for your plan and a test account	CreditPolicy includes API access in its custom Brokerage/Aggregator plan
Vendor-built CRM link	A link the vendor maintains between its product and a named CRM	A help article naming both products	Bulma loads your client’s details from your CRM into a scenario. Quickli receives deals sent from MyCRM. Cynario’s Charli runs inside Salestrekker 2.0
Custom build	A developer joins two systems to your specification	A signed-off scope and a person responsible for fixing it when it breaks	Bulma’s Enterprise plan includes custom integrations
Copying by hand	A staff member pastes checked text into the client file	Your file-note procedure	Works with every tool here

Get your network or aggregator to write a specification before anyone builds a connection to a policy tool. It must cover these points, whichever vendor supplies the tool.

• The scenario fields sent, limited to the minimum-data template
• A citation and the policy’s effective date with every answer
• Which roles can send a request, see an answer or approve it
• What the user sees when a lender is missing, a request fails or the service is offline

A failed request must show an error on screen. It must never come back as a blank answer or an old one.

When the connection is down, open the lender’s own policy document or broker portal instead. Save the passage with the date you read it, and send it through the usual broker review. Don’t accept a cached answer that doesn’t show its effective date.

Build a research record that stays in your client’s file whichever tool produced it. It holds these items.

• Which version of the scenario it covers, and when each run happened
• The lenders you assessed, and those you ruled out with the reason
• Each cited source with its date
• Questions still open, and anything that depends on servicing
• The name of the broker who approved it

Treat export of this record as a requirement you give each vendor. Count it as a feature only once the vendor documents it.

Compare Scenario Planning Software

Scenario planning software on this list holds servicing numbers, policy answers or both in one place. The table compares how the five specialist tools capture a scenario, keep its history, compare lenders, set permissions and export results.

Requirement	Bulma	CreditPolicy	Quickli	Thryvve	Cynario
Scenario capture	Whole scenario entered once, typed in or filled from uploaded payslips, a fact find or your CRM	Client profile built from notes and supplied information	Structured servicing inputs, auto-filled by Doc Handler on Pro	Scenario question in chat, with payslip upload	Scenario question in chat, by email or inside Salestrekker 2.0
Version history	Searchable conversation history, shared on Team. Change one fact to see the lender list and borrowing power move	Saved chats and scenarios, shared on Team	Duplicate a scenario to compare changes	None documented, and client details aren’t kept past the session	Archived conversations
Lender comparison	Policy check and borrowing power across 52+ lenders, grouped by standard fit, fit with conditions or exception	Policy research across 96 brands and residential servicing comparison	Servicing across 51 or more lenders, with Jiffi AI on Pro	Market scan and side-by-side comparison across about 30 lenders	Assessment against about 40 residential lenders
Permissions	Five members included on Team, extra seats for a fee and team usage analytics. Unlimited members on Enterprise	Administrator curates the lender library on Team	Free administrator and view-only users, and only the owner shares scenarios	Own login for each member, each with full access	Subscriber adds or removes users and sets their access
Export and connections	Copy an answer with its sources into file notes, or share a conversation. CRM integration, plus custom integrations on Enterprise	Export from the generated document library, API access on the custom plan and MCP connections	Print to PDF, EasyCalc exports and deals sent from MyCRM	No export documented	Answers can be downloaded for file notes. Works inside Salestrekker 2.0

For the aged-care worker, Quickli holds the $78,000 income and $420 car loan as servicing inputs, while Thryvve and Cynario hold her casual-income question and its answer. Bulma checks her whole scenario against each lender’s policy and works out her borrowing power at each one. CreditPolicy can hold her servicing inputs and policy question in one client profile.

Keep the version record in your client’s file whichever tool you use, because it shows which facts each result relied on. Quickli’s duplicate function keeps the original scenario beside the changed copy. Bulma reruns its policy check and borrowing power when you change one fact, such as time in the job.

The lender still runs the final serviceability calculation and credit assessment, and you lodge through your aggregator’s platform as usual. Treat any AI or third-party servicing result as a guide until the lender’s own assessment confirms it.

File the reviewed scenario, its version number and any unanswered questions with your client’s records. For residential files that need policy fit and borrowing power together, Bulma is the first choice because the same scenario produces a lender shortlist, conditions and quoted evidence. If that’s the job your brokerage needs covered, try Bulma free.