MAKO
Trove AI (formerly MAKO) · Coding · Business
MAKO, now Trove AI, is an AI associate for investment firms that reads your firm's own documents to screen deals, run diligence and build portfolio reports.
About MAKO
What Is MAKO
MAKO is an AI associate built for investment firms, and since October 2025 it trades under the name Trove AI. Instead of holding a chat in a blank window, it connects to the places your firm already stores its work, such as deal files, emails, CRM records and past analyses, and answers questions against that material. The pitch is narrow on purpose. Trove targets private equity first, where the day-to-day job is reading thousands of scattered documents, pulling buried metrics and packaging findings under deadline.
The problem it goes after is a memory one. General assistants reset every morning and know nothing about your firm, so a partner asking for a screen of a new target gets back the answer of a smart stranger. Trove keeps a living index of the companies, people and relationships a firm tracks, so context builds up instead of restarting. The company says clients open it more than a dozen times a week on average, a figure it reports grew 86% over three months.
Two limits matter before you commit. First, it is an enterprise product sold through demos, with no public price list and no self-serve signup, so small teams and individual investors are not the target. Second, the underlying model still makes mistakes, which is why every output cites the document it came from so a person can check the source.
Getting Started
- Request a demo from the Trove AI team and walk them through the workstreams you want covered, such as deal screening or portfolio reporting
- Connect your firm's data sources, mainly the CRM and file sharing apps you already run, in a setup the company describes as taking about 30 minutes
- Have the team deploy the platform inside your own cloud environment so documents stay on your systems
- Run your first task, like a deal screen or a quarterly portfolio report, and adjust the metrics and formats to match how your firm works
Product Information
A quick look at MAKO's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Private equity investors
- Portfolio operations teams
- Investment professionals at asset managers and professional services firms
Tasks
- Deal screening
- Due diligence synthesis
- Portfolio monitoring and benchmarking
- Historical metric retrieval
Scenarios
- Preparing for an investment committee meeting
- Building a quarterly portfolio report
- Checking a new market
- Supporting an associate who just joined
Key features
Search Across Your Own Firm Data
Trove connects to the CRMs and file sharing apps a firm already uses and answers questions against that material, with no upload step and no pre-cleaning. It reads deal files, emails and past analyses together, so a request about a company draws on everything the firm has stored about it. The company says setup takes about 30 minutes.
Finance-Specific Knowledge Graph
Financial data is messy and heavily interconnected, and plain keyword search struggles with it. Trove builds a knowledge graph that organizes material around companies, people and markets, which lets agents run more useful retrieval and analysis. This graph is the layer that separates a firm-aware assistant from a general chatbot.
Context-Aware Agents
The agents handle multi-step work the way an associate would, from screening a new opportunity to assembling a report. The company builds and maintains custom agents for each firm's common workstreams, and points to deal screening, diligence and portfolio monitoring as the core three. Because the agents work from the firm's own context, early output tends to match house formats more closely than a blank-slate assistant.
KPI and Benchmarking Dashboards
Firms get dashboards that track portfolio company KPIs and flag risks, compare a holding against sector peers, past deals and the active pipeline, and score bankers, service providers and lenders. Views roll up to firm level for leadership decisions, and they update as the underlying data changes rather than being rebuilt by hand.
Auditable Answers
Every answer cites the source document it drew from, so a reviewer can open the original and verify the claim instead of trusting the output blindly. For teams that have to defend a number in an investment committee, this traceability is the feature that makes the tool usable in real decisions.
Private Cloud Deployment and Security
Trove runs inside the customer's own cloud environment, an approach the company calls cloud-prem, so data stays on the firm's systems. It holds SOC 2 Type II certification, encrypts data with TLS 1.2+ in transit and AES-256 at rest, and states that it never uses customer data to train models. Firms that cannot send documents to a shared public service get a workable path here.
Trove MCP for Existing Tools
An MCP connection lets the team's existing assistants, including Claude and ChatGPT, reach the firm's context through one link. Trove lists this as coming soon rather than shipping today. The goal is to avoid a rip-and-replace decision, so a firm keeps the tools it likes and adds its own knowledge on top.
Pros and cons
Pros
- Answers are grounded in the firm's own documents and cite their source, which makes outputs easier to check
- Deployment aimed at roughly 30 minutes with pre-built connectors and no data cleaning, a light lift next to typical enterprise rollouts
- Private cloud, SOC 2 Type II and no training on customer data answer the main security objections in finance
- Specialized finance knowledge graph handles interconnected deal data better than generic search
- Vendor builds and maintains custom agents for each firm's workstreams
Cons
- No public pricing and no free or self-serve tier, so cost is only known after a sales conversation
- Built around private equity first, which means teams in other finance roles may find less fit and less custom work
- No public API today, so programmatic access depends on the MCP integration that is still listed as coming soon
- Accuracy still depends on the underlying models, and a wrong number can slip through if a reviewer skips the cited source
Frequently asked questions
MAKO, now Trove AI, is used to search a firm's own knowledge and turn it into work products: deal screens, due diligence summaries, portfolio reports and benchmark dashboards. It is for investment firms that want an assistant grounded in their own files rather than a general chatbot.
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