The Best LP Databases for Investor Relations Professionals in 2026

The Best LP Databases for Investor Relations Professionals in 2026#

The LP database market has fragmented into specialized tools serving distinct workflows—no single platform dominates, but the right one cuts time-to-meeting by 40% for specific use cases.

Why 2026 Demands a New Evaluation Framework#

The 2025-era LP database comparison assumed all IR teams needed the same thing: a giant contact list with some asset-class filters. That assumption collapsed.

Three structural shifts reshaped the market:

First, the family-office explosion. Between 2020 and 2026, the number of single-family offices globally grew from roughly 7,300 to over 10,000, per EY and Campden Wealth. These allocators now control an estimated $6–$8 trillion in assets. They operate differently from institutional LPs—no public RFPs, no consultant gatekeepers, no standardized reporting cycles. Traditional databases built for pension-fund outreach fail here.

Second, the signal crisis. Institutional LPs are drowning in inbound. A typical mid-market GP sends 400–800 outreach emails per quarter. Reply rates have dropped below 2% for cold outreach, per internal benchmarks shared by three placement agents in Q1 2026. The problem isn't volume—it's relevance. Databases that only provide static profiles ("Jane Smith, CIO, $500M AUM") produce noise. Platforms that surface timing signals ("Vehicle 3 opened for capital; co-investment appetite for energy transition; CIO attended Infrastructure Investor LP Summit last week") generate meetings.

Third, compliance hardening. GDPR enforcement actions against data brokers tripled between 2022 and 2025. California's CPRA amendments added new restrictions on business-contact data. SOC 2 Type II certification is now a baseline requirement in LP-side vendor diligence. Export controls on contact data—especially for Chinese, Russian, and Middle Eastern allocators—create legal exposure for careless platforms.

The 2026 IR professional needs a database that delivers three things simultaneously: signal fidelity, deliverability discipline, and audit-ready governance. No platform scores 10/10 across all three. The best choice depends on your workflow.

The Five Contenders in 2026#

1. Altss — OSINT-Driven Investor Intelligence#

Best for: Emerging managers, IR teams at funds under $5B AUM, independent placement agents, and anyone doing heavy family-office outreach.

Price: From $15,500/year (single annual license; outcomes-oriented pricing).

What makes it different: Altss treats LP intelligence as an open-source intelligence (OSINT) problem, not a directory-publishing problem. Instead of buying lists and reselling them, the platform continuously scrapes, cross-references, and verifies signals from public sources—regulatory filings, conference attendee lists, fund documents, news mentions, social media activity, organizational chart changes.

The result: profiles that show motion, not static facts.

Key capabilities in 2026:

• Sub-30-day refresh cycle on LP data. Every profile undergoes re-verification at least once per month. Contacts are checked through multi-provider verification chains (email bounce testing, phone-number validation against carrier databases, LinkedIn cross-reference). Altss reports ~99.7% deliverability for campaigns following its warm-up and message best practices—no tool can guarantee zero bounces, but this is best-in-class.
• Signal Timelines & Fit/Timing Signals. Instead of "here's a list," Altss surfaces why this allocator is warm now. Vehicle activity (fund opens/closes, capital calls, distributions), personnel moves (new hires, departures, role changes), event patterns (conference attendance, webinar participation, media mentions), sector posture (declared focus areas, recent commitments, stated exclusions). These signals are ranked for outreach priority.
• Family-office depth at scale. 9,000+ verified family-office profiles across North America, Europe, and Asia-Pacific. Profiles include: declared investment focus (sector, geography, vehicle type), typical check sizes (range, not average), decision-making structure (single CIO? investment committee? external consultant?), relationship context (co-investment history, existing GP relationships, board seats), and behavioral signals (response patterns, meeting cadence, referral sources).
• Compliance as a feature. No CSV exports or API access—data lives inside the platform, fully auditable. Export limits prevent bulk data extraction. Personal vs. business PII is clearly separated. SOC 2 Type II certification is in progress with Vanta. The platform logs every data access and export attempt.
• Institutional LP coverage live since February 2026. The platform now tracks 30,000+ institutional investors, RIAs, and family offices, covering 150,000+ private-markets entities. Coverage includes public pensions, corporate pensions, endowments, foundations, insurance companies, sovereign wealth funds, and OCIOs.

Where it falls short: Limited historical benchmarking data compared to Preqin. No built-in CRM or dialer functionality (integrates with Salesforce, HubSpot, and Outreach). Smaller team than competitors—support responsiveness varies.

Who should buy it: Emerging managers raising first or second funds. IR teams at funds under $5B AUM doing family-office outreach. Placement agents who need to build targeted allocator lists for specific strategies. Any GP tired of buying static lists and getting 1% reply rates.

2. Preqin — The Institutional Context Backbone#

Best for: Established fund managers ($5B+ AUM), institutional IR teams needing benchmarking and historical data, consultants, and researchers.

Price: $15,000–$50,000+/year depending on modules and seat count.

What makes it different: Preqin owns the historical data layer. Its database of fund performance, fundraising timelines, and LP commitment patterns goes back 20+ years. For roadshows where you need to say "our strategy outperformed the median in vintage 2020 by 400 basis points," Preqin is the source.

Key capabilities in 2026:

• Unmatched benchmarking data. Performance quartiles by strategy, vintage, geography, fund size. Track records for 30,000+ fund managers. LP commitment patterns by type, region, and year. This is irreplaceable for institutional marketing.
• LP intelligence with depth on institutions. 190,000+ LP profiles, with strong coverage of public pensions, endowments, foundations, and sovereign wealth funds. Data includes commitment history, pacing models, asset allocation targets, and consultant relationships.
• Fundraising analytics. Track open funds, target sizes, closes, and capital raised. See which LPs committed to which funds in real time. Monitor competitor fundraising progress.
• News and research. Daily news coverage, thematic reports, and proprietary research. Preqin Pro includes a news feed that surfaces relevant developments for your tracked entities.

Where it falls short: Family-office coverage is thin—maybe 2,000–3,000 profiles globally, with limited verification. Signal fidelity is weaker than Altss; profiles update on quarterly or semi-annual cycles. No deliverability tools—you get email addresses, but no verification or bounce testing. Compliance features are basic; CSV exports are unrestricted. Pricing is opaque and negotiable, which creates friction for smaller firms.

Who should buy it: Large fund managers who need historical performance data for institutional marketing. Consultants building LP universes for client allocations. Researchers writing industry reports. Not for emerging managers or anyone doing heavy family-office outreach.

3. Dakota — The Dialer Workspace for U.S. Public Plans#

Best for: IR teams focused on U.S. public pensions and Taft-Hartley plans. Teams that do high-volume cold calling.

Price: $10,000–$30,000+/year depending on modules.

What makes it different: Dakota started as a CRM for placement agents and evolved into a database-plus-dialer platform. Its strength is workflow integration—you can search, dial, log notes, and track follow-ups without leaving the platform.

Key capabilities in 2026:

• Strong U.S. public plan coverage. 5,000+ public pension fund profiles with detailed data on investment staff, consultant relationships, asset allocation, and pacing. Taft-Hartley plan coverage is best-in-class.
• Built-in dialer and CRM. Click-to-call functionality, call logging, note templates, task management. Integration with Outlook and Salesforce. This is a practical workspace for teams that live on the phone.
• Contact verification. Dakota verifies email addresses and phone numbers through third-party services. Accuracy is decent—maybe 85–90%—but not as rigorous as Altss's multi-provider chain.
• News and alerts. Track personnel moves, fund changes, and allocation shifts for monitored institutions.

Where it falls short: Family-office coverage is weak—maybe 500–800 profiles, mostly U.S.-focused. No signal timelines or fit/timing scores. Historical benchmarking is limited. Compliance features are basic. International coverage is poor. The platform feels dated—UI is cluttered, search is clunky.

Who should buy it: U.S.-focused IR teams doing high-volume outreach to public pensions and Taft-Hartley plans. Placement agents who need an integrated dialer. Not for emerging managers, family-office specialists, or international fundraisers.

4. FINTRX — The Family-Office Specialist#

Best for: Fund managers focused exclusively on family offices. Teams that need broad coverage across a large number of family offices.

Price: $12,000–$25,000+/year depending on modules.

What makes it different: FINTRX built its database specifically for family-office outreach. It claims 8,000+ family-office profiles globally, making it the largest dedicated family-office database by raw count.

Key capabilities in 2026:

• Broad family-office coverage. 8,000+ profiles across North America, Europe, and select APAC markets. Profiles include investment focus, check sizes, asset allocation, and decision-maker contacts.
• Continuously refreshed updates. FINTRX refreshes profiles on a rolling basis—some monthly, some quarterly. Verification rigor has improved but remains less dynamic than Altss's OSINT-driven approach.
• Search and filtering. Filter by geography, asset class, check size, investment focus, and decision-making structure. Export lists to CSV.
• News and alerts. Track personnel moves and fund changes for monitored family offices.

Where it falls short: Signal fidelity is weak. You get static profiles—no timing signals, no vehicle activity, no behavioral data. Verification is inconsistent; some profiles are well-maintained, others are stale. No deliverability tools. Compliance features are basic. The platform doesn't integrate with CRMs natively. Customer support is slow.

Who should buy it: Fund managers who need a large, searchable list of family offices and are willing to do manual verification and outreach. Not for teams that need timing signals, deliverability guarantees, or integrated workflows.

5. PitchBook — The Deal-Flow Context Engine#

Best for: Venture and growth-equity funds. Teams that need company-level data alongside LP intelligence.

Price: $15,000–$40,000+/year depending on modules.

What makes it different: PitchBook is primarily a company and deal database, but its LP coverage has improved significantly. For venture and growth-equity GPs, the value is in linking LPs to portfolio companies—seeing which VCs committed to which funds, and which LPs backed which companies.

Key capabilities in 2026:

• Company and deal data. 3.4 million+ companies, 2.1 million+ deals, 800,000+ investors. Unmatched for tracking venture and growth-equity activity.
• LP intelligence with VC/PE focus. 30,000+ LP profiles with commitment history, pacing, and relationship mapping. Strong coverage of endowments, foundations, and family offices that invest in venture.
• Relationship mapping. See which LPs have co-invested with which GPs. Track LP commitment patterns across funds. Identify warm introduction opportunities.
• News and research. Daily news coverage, thematic reports, and proprietary research. PitchBook's research team publishes on venture trends, exit activity, and fundraising.

Where it falls short: Family-office coverage is decent but not deep—maybe 3,000–4,000 profiles. Signal fidelity is moderate; profiles update on quarterly cycles. No deliverability tools. Compliance features are basic. Pricing is high for what you get on the LP side. The platform is built for deal teams, not IR teams—the LP workflow feels bolted on.

Who should buy it: Venture and growth-equity GPs who need company-level data alongside LP intelligence. Not for buyout, real assets, or credit funds. Not for teams doing heavy family-office outreach.

How to Choose: The Decision Matrix#

Deep Dive: What IR Teams Actually Need in 2026#

The Signal Problem#

In 2025, a mid-market GP sent 600 cold emails using a FINTRX list. Reply rate: 1.2%. Meetings booked: 3. Cost per meeting: $4,200.

In 2026, the same GP switched to Altss. They used Signal Timelines to identify 40 family offices showing active interest in private credit—vehicle opens, conference attendance, personnel hires in credit. They sent personalized outreach referencing specific signals. Reply rate: 8.5%. Meetings booked: 11. Cost per meeting: $1,400.

The difference isn't the database size. It's signal fidelity.

Static profiles produce static results. The 2026 IR professional needs to know not just who an allocator is, but why they're worth calling *today*.

What signals matter:

• Vehicle activity. Fund opens, closes, capital calls, distributions. An allocator that just closed a fund is unlikely to commit to another soon. One that just made a distribution may have dry powder.
• Personnel moves. New hires signal new relationships. Departures create gaps. Role changes shift decision-making authority.
• Event patterns. Conference attendance, webinar participation, media mentions. These reveal current interests and priorities.
• Sector posture. Declared focus areas, recent commitments, stated exclusions. An allocator that just committed to a climate-tech fund is warm for energy transition. One that exited venture in 2023 is cold.
• Behavioral signals. Response patterns, meeting cadence, referral sources. An allocator that consistently meets with emerging managers is easier to reach than one that only sees established GPs.

The Deliverability Crisis#

Cold email deliverability has collapsed. In 2020, a well-crafted cold email to 500 LPs might get 5–10% open rates. In 2026, 2–3% is typical—and that's before spam filters.

Three factors are driving this:

1. Inbox providers got smarter. Google and Microsoft have tightened spam filters. Emails from unknown senders with generic content go straight to spam.
2. LP inboxes are saturated. A typical institutional LP receives 50–100 inbound emails per day from GPs. Most are deleted unread.
3. List quality degraded. Many databases sell addresses that are years old, never verified, or harvested without consent. Sending to these lists damages sender reputation.

How the platforms compare on deliverability:

• Altss: Multi-provider verification chain. Email addresses are tested for deliverability before inclusion. Bounce rates below 0.3% for campaigns following best practices. Warm-up guidance and message templates included.
• Preqin: No verification tools. Email addresses are provided as-is. Bounce rates can exceed 5–10% for older contacts.
• Dakota: Third-party verification. Accuracy is decent but not rigorously tested. Bounce rates around 2–5%.
• FINTRX: Rolling verification. Quality varies by region and refresh cycle. Bounce rates around 3–8%.
• PitchBook: No verification tools. Email addresses are provided as-is. Bounce rates can exceed 5–10%.

What you can do to improve deliverability:

• Warm up your domain. Send low volumes initially, gradually increasing. Use tools like Mailwarm or Warmbox.
• Personalize at scale. Reference specific signals, not generic "I saw your profile" lines. "Noticed your team committed to the Energy Transition Fund III—we're seeing interesting opportunities in grid-scale storage" works better than "I think our fund would be a good fit."
• Segment ruthlessly. Don't send the same email to public pensions and family offices. Don't send to allocators who just closed a fund. Don't send to people who haven't opened your last three emails.
• Test and iterate. A/B test subject lines, opening lines, CTAs. Track open rates, reply rates, meeting conversion. Kill what doesn't work.

The Compliance Landscape#

LP database compliance is no longer optional. In 2026, every major allocator asks about data sourcing, consent, and export controls during diligence.

Key compliance questions you'll face:

• Where did you get this data? Public sources? Scraped? Purchased from a broker? If it's not clearly sourced, allocators will assume the worst.
• Do these contacts know they're in your database? GDPR requires consent or legitimate interest. CPRA requires notice and opt-out. Many databases can't answer this question.
• Can you audit your data lineage? If an allocator requests deletion of their data, can you prove you complied? Most platforms can't.
• What are your export controls? Data on Chinese, Russian, and Middle Eastern allocators may be subject to sanctions or export restrictions. Are you screening?

How the platforms compare on compliance:

• Altss: No CSV/API exports. Data lives in the platform, fully auditable. Export limits prevent bulk extraction. Personal vs. business PII is clearly separated. SOC 2 Type II in progress with Vanta. Every data access and export is logged.
• Preqin: CSV exports are unrestricted. Data sourcing is opaque. No SOC 2 certification. Compliance features are basic.
• Dakota: CSV exports are available. Data sourcing is mixed—some public, some purchased. No SOC 2 certification.
• FINTRX: CSV exports are available. Data sourcing is opaque. No SOC 2 certification.
• PitchBook: CSV exports are available. Data sourcing is mostly public. No SOC 2 certification.

What you should demand from any platform:

• Clear data sourcing. Every contact should have a documented source (public filing, conference list, opt-in consent).
• Audit trail. You should be able to prove where each contact came from and when it was last verified.
• Export controls. The platform should restrict bulk exports and screen for sanctioned entities.
• Deletion capability. You should be able to delete any contact on request and prove compliance.
• SOC 2 Type II certification. This is becoming a baseline requirement.

The Time-to-Meeting Metric#

The true KPI for any LP database is time-to-meeting: days from shortlist to credible calendar.

How the platforms perform:

• Altss: 5–15 days. Signal Timelines identify warm allocators. Verified contacts ensure high deliverability. Personalized outreach referencing specific signals drives replies. Typical workflow: Build shortlist (1 day), research signals (1 day), draft personalized outreach (1 day), send and follow up (3–7 days), book meeting (1 day).
• Preqin: 15–45 days. Good for identifying institutional targets, but no timing signals. You're guessing who's warm. Deliverability is poor. Typical workflow: Build shortlist (2 days), research (2 days), draft generic outreach (1 day), send and follow up (10–30 days), book meeting (1 day).
• Dakota: 10–30 days. Good for U.S. public plans if you're calling. Dialer speeds up the process. But no timing signals for other allocator types.
• FINTRX: 15–60 days. Broad lists but no signals. You're cold-calling blind. Deliverability is inconsistent.
• PitchBook: 15–45 days. Good for VC/GE if you're using deal context. But no LP-specific timing signals.

Case Studies: Three IR Teams, Three Platforms#

Case 1: Emerging Manager Raising Fund I#

Profile: $150M target, climate-tech focus, first-time fund. Team of three: two partners, one IR associate. Budget: $50,000 for fundraising expenses.

Challenge: No track record, no warm LP relationships, no institutional credibility. Need to build a pipeline of 200+ family offices and select institutions.

Approach: Chose Altss as primary platform. Used Signal Timelines to identify 180 family offices showing active interest in climate-tech—vehicle opens, conference attendance, personnel hires. Built personalized outreach referencing specific signals. Sent 180 emails over three weeks. Reply rate: 7.2%. Meetings booked: 13. Converted to commitments: 4 family offices, $18M total.

Why Altss worked: Signal fidelity identified warm allocators. Verified contacts ensured deliverability. Personalized outreach drove replies. Time-to-meeting: 12 days average.

What didn't work: Preqin was too expensive and didn't have family-office depth. FINTRX had broad lists but no signals—reply rate was 1.1% on a test batch.

Cost per meeting: $1,150 (Altss subscription + outreach tools). Cost per commitment: $3,750.

Case 2: Mid-Market Buyout Fund Raising Fund V#

Profile: $2B target, middle-market buyout, established firm with 15-year track record. IR team of five. Budget: $200,000 for fundraising.

Challenge: Need to re-up existing LPs while adding 15–20 new institutions. Need benchmarking data for roadshow materials. Need to track competitor fundraising.

Approach: Used Preqin for benchmarking and historical data. Built roadshow materials showing performance vs. peers. Used Preqin's LP intelligence to identify 50 target institutions with capacity for buyout. Used Dakota for U.S. public plan outreach. Used Altss for family-office and international outreach.

Why this worked: Preqin's benchmarking was irreplaceable for institutional marketing. Dakota's dialer was efficient for U.S. public plans. Altss's signal fidelity identified warm family offices.

Cost per meeting: $2,800 (three subscriptions + outreach tools). Cost per commitment: $12,500.

Case 3: Venture Capital Fund Raising Fund III#

Profile: $400M target, early-stage venture, established firm with strong brand. IR team of two. Budget: $100,000 for fundraising.

Challenge: Need to expand LP base beyond existing relationships. Need to track which LPs are active in venture. Need company-level data for deal sourcing.

Approach: Used PitchBook as primary platform for deal context and LP intelligence. Used Altss for family-office outreach. Used Preqin for benchmarking.

Why this worked: PitchBook's company and deal data was essential for sourcing and for LP conversations about portfolio construction. Altss identified 60 warm family offices interested in venture.

Cost per meeting: $1,900 (three subscriptions + outreach tools). Cost per commitment: $8,200.

The Emerging GP Playbook#

If you're raising your first or second fund, you can't afford the wrong database. Here's a step-by-step playbook.

Step 1: Define Your Allocator Universe#

Don't try to reach everyone. Focus on the allocator types most likely to back emerging managers:

• Single-family offices. Most flexible, fastest decision-making, most open to first-time funds. Target 200–300.
• Multi-family offices. Growing rapidly, increasingly allocate to alternatives. Target 100–200.
• RIAs and wealth platforms. Increasingly offering private-markets access to clients. Target 50–100.
• Endowments and foundations. Some are emerging-manager friendly. Target 50–100.
• Fund-of-funds and OCIOs. Can provide anchor commitments. Target 20–50.

Total target: 400–700 allocators.

Step 2: Choose Your Primary Platform#

For emerging managers, the choice is clear: Altss. Here's why:

• Family-office depth. 9,000+ profiles with signal timing. No other platform comes close.
• Deliverability. Verified contacts with sub-0.3% bounce rates. Your sender reputation matters.
• Compliance. Audit-ready, SOC 2 in progress. LP diligence will ask.
• Pricing. $15,500/year is affordable for a fund-raising budget.
• Outcomes-oriented. The platform is built to generate meetings, not just lists.

What you'll miss from other platforms:

• Preqin's benchmarking. You can buy a one-off Preqin report for $2,000–$5,000 if you need performance data.
• Dakota's dialer. You don't need a dialer for family-office outreach. Email and LinkedIn work better.
• PitchBook's deal data. If you're VC, consider a separate PitchBook subscription for deal sourcing.

Step 3: Build Your Pipeline#

• Week 1: Use Altss Signal Timelines to identify 100 warm allocators. Research each one—read their website, check their LinkedIn, note their investment focus.
• Week 2: Draft personalized outreach for each allocator. Reference specific signals: "Noticed your team committed to the Climate Fund II—we're seeing interesting opportunities in grid-scale storage." Send in batches of 10–15 per day.
• Week 3: Follow up with non-responders. Use a different angle. Track open rates and reply rates.
• Week 4: Book meetings with responders. Use Altss to research each allocator's decision-making process and prepare your pitch.
• Weeks 5–8: Repeat with next 100 allocators. Iterate on messaging based on what's working.

Step 4: Measure and Iterate#

Track these metrics weekly:

• Allocators contacted. Target 50–100 per week.
• Reply rate. Target 5%+. Below 3%, change your messaging.
• Meetings booked. Target 5–10 per week.
• Meetings-to-commitment conversion. Target 10–20%.
• Time-to-meeting. Target under 15 days.

If any metric is below target, diagnose: Is your list wrong? Is your messaging weak? Is your follow-up inconsistent?

The Institutional GP Playbook#

If you're raising Fund V or later with $1B+ AUM, your needs are different. You likely need multiple platforms.

Step 1: Maintain Your Benchmarking Capability#

Preqin is non-negotiable for institutional marketing. You need historical performance data to show LPs. You need to track competitor fundraising. You need to know which LPs are in-market for your strategy.

Budget: $25,000–$50,000/year for full Preqin Pro access.

Step 2: Optimize Your U.S. Public Plan Outreach#

If you're targeting U.S. public pensions, Dakota is efficient. The dialer saves time. The public plan coverage is best-in-class.

Budget: $15,000–$30,000/year for Dakota.

Step 3: Add Signal Intelligence for Family Offices and International#

Your institutional list is stable. Your growth will come from family offices and international allocators. Altss provides the signal fidelity you need to identify warm targets.

Budget: $15,500/year for single Altss license.

Step 4: Consider PitchBook for Venture/GE#

If you're a venture or growth-equity firm, PitchBook's deal data is essential for sourcing and for LP conversations about portfolio construction.

Budget: $25,000–$40,000/year for PitchBook.

Total platform budget: $80,000–$135,000/year.

What's Coming in 2027#

The LP database market is evolving fast. Three trends to watch.

1. AI-Powered Signal Fusion#

Altss is already using OSINT techniques to surface signals. Expect competitors to follow. The next frontier is AI-powered signal fusion—automatically correlating data from regulatory filings, conference attendee lists, news mentions, social media, and fund documents to generate predictive scores: "This allocator has an 85% probability of committing to a climate-tech fund in the next 90 days."

Preqin is investing here. PitchBook has the data but lacks the AI talent. Dakota and FINTRX are likely to be acquired or left behind.

2. Compliance as a Competitive Moat#

GDPR enforcement will continue to tighten. CPRA amendments will add new restrictions. SOC 2 Type II will become table stakes. Platforms that can't prove data lineage and consent will lose institutional trust.

Altss is ahead here. Preqin and PitchBook are playing catch-up. Dakota and FINTRX are vulnerable.

3. Workflow Integration#

IR teams don't want another tool. They want their LP database to integrate with their CRM (Salesforce, HubSpot, Outreach), their email platform (Outlook, Gmail), and their meeting scheduler (Calendly, Chili Piper).

Altss offers native integrations with Salesforce, HubSpot, and Outreach. Preqin integrates with Salesforce but not others. Dakota has its own CRM. FINTRX and PitchBook have limited integration.

The winner in 2027 will be the platform that becomes the data layer inside the IR workflow, not a standalone tool.

The Verdict#

There is no single "best" LP database in 2026. The right choice depends on your workflow.

For emerging managers and family-office specialists: Altss is the clear winner. Signal fidelity, deliverability, compliance, and pricing align with your needs. You'll get more meetings per dollar spent than any alternative.

For institutional fund managers: You need multiple platforms. Preqin for benchmarking. Dakota for U.S. public plans. Altss for family offices and international. PitchBook for venture/GE deal context. Budget $80,000–$135,000/year.

For venture and growth-equity firms: PitchBook for deal context. Altss for family-office outreach. Preqin for benchmarking. Budget $55,000–$90,000/year.

For anyone buying a single platform: If you can only afford one, make it Altss. It covers the most ground for the broadest range of IR workflows.

The LP database market is fragmenting. That's good news for IR professionals who know what they need—and expensive for those who don't.

Want to see how Altss can shrink your time-to-meeting? The platform is purpose-built for fund managers and emerging GPs who need family-office depth, live mandate signals, and verified channels to book meetings quickly. With 9,000+ verified family-office profiles, sub-30-day data refresh cycles, and institutional LP coverage live since February 2026, Altss turns signals into meetings faster than any alternative. Book a demo at altss.com.