See every dealworth seeing,before anyone else.

    Proprietary sourcing, banker coverage, and a pipeline your investment committee trusts. We build the CRM, data, and AI layer that turns your team's relationships and thesis into a repeatable deal engine.

    Plan your deal engine →

    Skydog is the partner of choice for asset managers overseeing $500B+ in AUM.

    Carnelian Energy Capital
    Cerberus
    Eagle Point Credit
    $300B AUM ALTS FIRM
    HPS
    Lead Edge Capital
    LLR Partners
    $100B PE FIRM
    Mercury
    Series X Capital
    Carnelian Energy Capital
    Cerberus
    Eagle Point Credit
    $300B AUM ALTS FIRM
    HPS
    Lead Edge Capital
    LLR Partners
    $100B PE FIRM
    Mercury
    Series X Capital
    01

    Where it breaks today.

    What we hear most from deal and origination teams before we start.

    01

    Relationships live in inboxes

    Who knows the founder, which banker owes you a look, and when you last spoke are scattered across personal inboxes. When someone leaves, the network leaves with them.

    02

    CIMs pile up unread

    Teasers and CIMs arrive faster than associates can read them. Good deals get a slow no, and bad deals eat a week of work.

    03

    Pipeline reviews are archaeology

    Stages are stale, passed deals have no reason recorded, and nobody can say which intermediaries actually send the deals you close.

    02 · The system we build

    Four layers. One system.

    The AI your team works in, the CRM underneath it, the overlay products that feed it, and the data you already have, connected and governed.

    LAYER 01

    What your team works in

    ClaudeOpenAIGrok

    AI triaging CIMs, building market maps, and drafting IC memos from your thesis, your past deals, and your diligence notes.

    LAYER 02

    CRM

    The system of record

    Salesforce

    Salesforce Financial Services Cloud, DealCloud, or Affinity, configured around companies, intermediaries, deals, and the relationships that connect them.

    Relationships captured from email and calendarIntermediary coverage and deal attributionStages and pass reasons that hold up in IC

    LAYER 03

    Overlay products

    Data and workflow on top

    PitchBookCompany, deal, and investor data
    S&P GlobalFinancials and comparables
    ClayThesis-driven lists and enrichment
    DealCloudDeal management, where you run it
    See the full Private Capital stack

    LAYER 04

    Your data

    Where the truth lives today

    Email & calendarData rooms & CIMsPast IC memosPortfolio company data

    Deal flow triage

    Every CIM read and scored before the first call.

    Inbound deals are read against your thesis the moment they arrive. The deal team sees fit, the relationship behind the deal, and similar deals you've already looked at, so the right ones get attention fast.

    • Thesis fit scoring with the reasons spelled out
    • The intermediary, relationship strength, and history on every deal
    • Similar past deals and pass reasons, pulled from your own CRM
    Deal flow · Inbound triage

    Project Atlas

    Strong fit

    Vertical software for dental groups · $18M EBITDA

    via Meridian Partners · R. Chen

    92

    Fit

    Why it fits

    85% recurring revenue

    Founder-owned, first institutional round

    Add-on angle for Fund III platform

    From your CRM

    Banker relationship: warm, 4 touches in 12 months

    Similar: Project Kestrel, passed on customer concentration

    Project Birch

    Partial fit

    Specialty chemicals distributor · $31M EBITDA

    via Calder & Co · J. Ortiz

    64

    Fit

    Project Cove

    Outside thesis

    Consumer subscription app · $6M EBITDA

    via Inbound

    21

    Fit

    Grok

    Project Atlas matches your vertical software thesis. The CIM summary and three questions for the banker are ready for review.

    Write the one-pager

    Illustrative example. Names and figures are fictional.

    03

    The agent menu

    The agents we build most often for deal and origination teams. If your team repeats it, we can build it.

    What changes

    What your team gets back.

    A network that stays with the company

    Relationships are captured as they happen, so coverage survives turnover and every partner can see who knows whom.

    A faster yes, and a faster no

    Every deal gets a structured first read on day one, so the team spends its time on the right ones.

    A pipeline IC trusts

    Current stages, recorded pass reasons, and source attribution turn pipeline reviews into strategy.

    Get Started

    Build the deal engine
    your thesis deserves.

    Plan your deal engine →

    FAQ

    Common questions

    Should we use DealCloud, Affinity, or Salesforce for deal flow?

    It depends on team size, how much you rely on relationship intelligence, and whether fundraising and portfolio work live in the same system. We've built on all three and compare them in our DealCloud vs. Affinity vs. Salesforce guide.

    Can you capture relationships automatically from email?

    Yes. We set up email and calendar capture so interactions are logged against the right people and companies without manual entry, with controls for what stays private.

    Can AI really read CIMs accurately?

    AI is very good at a structured first read: extracting financials, summarizing the business, and checking fit against your criteria. We design it to cite the page behind every figure and leave the judgment to your team.

    How do you handle MNPI and information barriers?

    We mirror your information barriers in CRM permissions and AI tool access, so deal data is only visible to the people and agents cleared to see it.