Built for freelance devs + boutique dev shops + technical consultants

Cold email leads for freelance developers + dev shops. Every prospect has a real signal.

Freelance dev work compounds when you reach the company right at the moment they need exactly the work you do. Outbound-in-a-Box delivers 50–500 prospects with openers grounded in real technical signals. GitHub activity, stack changes, open dev roles, technical blog posts, infrastructure announcements. Reads like a peer. Converts way better than upwork-style spray.

Get a free 25-prospect sample → See pricing

Why signal-grounded outbound works for this vertical

Freelance dev outbound has unique leverage because technical signals are loud, specific, and directly indicative of work-fit:

Technical buyers respect technical fluency. A CTO can tell in 5 seconds whether you understand their stack. An opener that cites their actual repo, library, or recent technical decision earns the read. Anything generic gets deleted.
Open job postings = direct demand signal. If a company has 3 senior backend roles open + you're a senior backend freelancer, they have explicit budget allocated to the kind of work you do. Reach them with the question of whether contract is acceptable while they hire FT.
Project-based work has a clean buying moment. A company shipping a new product, migrating off a deprecated library, or rebuilding a critical system has a one-time need. Reach them in the planning window before they over-hire FT.

The signal types we use for freelance developers

Signal	Why it works
Open job postings (specific stack)	Companies hiring contract OR FT in your exact stack. Cite the open req + offer contract-to-bridge while they hire.
GitHub activity / open-source contributions	Highest-trust signal for technical buyers. Cite specific repo activity + tie to a relevant skill.
Recent technical blog post / talk	Indicates what they're working on + their technical taste. Reference + offer specific help.
Stack migration / framework adoption	Public announcements like "we're moving from Rails to Go". Direct demand for migration expertise.
Recently shipped product / public beta	Triggers iteration + scaling work. Cite the launch + the typical follow-on dev needs.
Funding round (Pre-A through B)	Triggers fast dev hiring + contract bridge needs. Cite round + likely upcoming roadmap work.

Example openers we've shipped

To: CTO · Series A B2B SaaS · 18 employees · stack: Rails + Postgres + Stripe · Brooklyn

Signal: GitHub showing active migration commits in the `payments/` subtree in March 2026 + a technical blog post on "why we're rebuilding our subscription engine."

Noticed the payments/ subtree refactor + the subscription-engine blog post. The rebuild from Stripe Billing primitives to your own subscription engine is the move most Rails/Stripe shops make right around Series A, and the part that usually surprises teams is the dunning + proration edge cases (especially mid-cycle plan changes with usage-based pricing). I've shipped the same migration for 4 Series A B2B SaaS shops in the last 18 months. Happy to share what the proration test matrix usually needs to cover before launch.

To: Engineering Manager · DTC e-commerce platform · ~40 engineers · Boston

Signal: Job posting on company careers page in March 2026: "Senior Backend Engineer, 6-month contract, Python/Django/Postgres preferred, focus on order-management-system rebuild."

Saw the senior-backend contract role on your careers page + the OMS-rebuild focus. Django + Postgres OMS rebuilds at DTC scale tend to live or die on the inventory-event-sourcing model (especially when the front-end is Shopify-style add-to-cart and the back-end needs eventual consistency across 6 warehouses). I've shipped 3 OMS rebuilds in the same shape. Happy to send 2-3 architecture options before you finalize the FT hire spec.

To: Founder · early-stage AI infra startup · ~8 employees · NYC

Signal: GitHub showing public benchmarks repo with active commit activity + Twitter thread in March 2026 about "deciding between vLLM and TGI for production inference."

Saw the benchmarks/ repo activity + the vLLM-vs-TGI thread. At your stage the inference-stack decision usually compounds into the next 12 months of latency-cost trade-offs (vLLM wins on continuous batching for variable-length input. TGI wins on per-request observability if you need it). I've shipped the production-inference rollout for 5 AI-infra companies at Series-Seed-to-A. Happy to share the benchmark methodology + cost model I use to decide vLLM vs TGI vs custom for the specific workload shape.

How to start

Two paths, depending on how convinced you are already:

Convinced: Buy Starter ($97 / 50 prospects) and ship within 24h. Refund-if-templated guarantee covers you if any opener reads canned.
Want to see quality first: Request a free 25-prospect sample. Same engine, smaller batch, 24h delivery, no card.
Need one tiny workflow fixed first: Reserve a $1 micro-automation slot for a script, CSV cleanup, scrape manifest, QA checklist, or handoff file. The $1 reserve is credited toward the first scoped fixed-price build.

Most freelance devs start with Starter ($97 / 50 prospects) targeting one stack-specific ICP (e.g. "Rails Series A SaaS hiring senior backend"). Given typical project sizes ($10k-$50k+), even a 1% conversion is 10x+ on the batch cost. Best practice: send 3-5 touches over 2 weeks, then reuse the same prospect list for adjacent project pitches later.

One small caveat

If your freelance niche is hyper-specialized (e.g. "WebAssembly compiler engineering"), the TAM may be too small for cold outbound to make sense. You'd burn through every relevant company in one batch. We're best fit for freelance specialties with TAMs of 500+ companies (Rails, Django, React, Node, Go, Python ML, etc.).

Try the engine on your real ICP

25 free prospects with personalized openers for your specific target buyer. 24h delivery. No card.

Request free sample → Reserve micro-automation for $1 Compare vs Apollo / Clay / Lemlist