DealFlow is an autonomous business-development engine we built for Debtworks, a capital-advisory firm. The team describes its buyer in plain English; that compiles into the playbook a fleet of agents run — sourcing, scoring, drafting, classifying replies, and moving the pipeline. A human approves the moments that matter. The machine does the rest.
Debtworks places debt for real companies. The team's edge is judgement — who to call, what to say, when a deal is worth chasing. But the motion that feeds it was manual: build a list, research each name, write the email, triage every reply, remember to follow up. The expertise was the bottleneck and the busywork at the same time.
Debtworks' real operating record — the domain reality DealFlow was built to scale, not replace.
Every stage of the sales motion — signal to outcome — captured on one surface, so the system learns what actually converts for this firm, in this market.
Apollo, CSV, and Tracxn imports deduped into a company graph, each contact scored against the firm's ICP by Claude.
Sequences drafted in the firm's tone from the rules document, sent on a warmed, isolated domain under daily caps.
Every reply classified into seven classes with confidence; a response drafted and queued for one-click human approval.
Approved drafts propose real calendar slots; the deal moves to Meeting booked the moment a time is taken.
Outcomes write to an immutable event log — the substrate that tells the firm which signals and angles actually close.
SIGNAL → OUTREACH → REPLY → MEETING → OUTCOME ↺ every outcome sharpens the next campaign
No filter builders, no settings sprawl. The team writes who they sell to the way they'd brief a new analyst. Claude parses it into a structured, versioned rules document — echoed back for confirmation — that drives sourcing, scoring, drafting, and every stage transition downstream.
"Founders and CFOs at Series A–C companies in India raising ₹20–150 Cr of debt. Worth a call the moment they close an equity round or post a finance hire."
ICP finance leaders · Series A–C · India SIGNALS EQUITY_ROUND_NEW w 1.0 FINANCE_HIRE w 0.8 STAGES New → Contacted → Replied → Qualified → Meeting → Outcome RULES REPLY=INTERESTED → QUALIFIED pinned · rules v3 · confirmed
The product owns the entire critical path — domains, DNS, sending, sourcing, classification, pipeline — so the firm does zero infrastructure work and approves only the decisions that are genuinely theirs to make.
Dedicated domain, DNS (SPF/DKIM/DMARC), SMTP and warm-up provisioned automatically. One bad campaign can never tank another tenant's reputation.
Every contact fit-scored 0–100 against the raw rules, with a one-line reason in the firm's own voice. Above threshold ships; borderline asks for a human eye.
Interested, objection, not-now, referral, unsubscribe, out-of-office, noise — each with confidence. Low confidence routes to a human; nothing is silently deleted.
Drafts wait for a click before sending under the firm's name. Edit distance is stored as training signal; a 10-second undo backs out any send.
"Add the founders at companies over 200 people" — typed in plain English, parsed, previewed against real data, and enrolled into the pipeline on confirm.
Postgres row-level security on every table; the app role can't bypass it. No query ever reads tenant from a request — only from a signed token.
Not a prototype. Real data, real performance, verified in production.
Operating history (₹240 Cr debt raised · 38 facilities closed · 6 hours per lead · 11 days term-sheet-to-draft) reflects Debtworks' actual record and pre-platform baseline. System figures (import volumes, the 16s→200ms board optimization, the ≤5-minute classification target, RLS isolation) are measured against the deployed build. Outbound performance figures are not claimed here; the engagement is in production and accruing its own results. Full detail under NDA.
We didn't sell Debtworks a tool to learn. We built the motion, wired it to their real data, and handed back a system that runs the outbound and gets sharper every week — code they own, no platform lock-in.
If there's a repeatable, expertise-heavy motion eating your team's hours, tell us about it. We'll come back with scope, timeline, and price — or an honest "not a fit."