Revenanas is a revenue engineering agency. We work with revenue teams to fix their data, build the workflows that drive efficiency, and put AI to work.
Over the last year and a half, Clay has become an essential part of the revenue operations stack — it's where you get your data, where you orchestrate it, and where you own the outcome. Here's the argument for why.
Not long ago, good data meant juggling six contracts, a stack of tools that didn't talk, and a spreadsheet nobody trusted. Clay replaced that. It's now the single place revenue teams both host their workflows and get their data — one canvas where enrichment, scoring, and routing live next to the records they act on. New to it? Start with what Clay is.
Connect every tool and agree on what good data looks like. Dead and duplicate records caught before a rep sees them, one fit-and-intent score on every account — a single source of truth the whole stack inherits.
Run the unscalable, hand-crafted play at scale. Research a thousand accounts the way you used to research ten — then fire personalised, signal-timed outreach off what you find.
Every team wants to bring AI into their revenue work. Most can't — they don't have the tool to do it, or a scalable way to run it with governance across models, across prompts, and reusable from one use-case to the next.
Clay is where that changes. You get access to every major model in one place, run on your own keys and credits, and test without signing a new contract for each one. And because everything is workflow-based — built left to right — you can see exactly what each AI prompt produces, then layer the next one on top. That's also where governance lives: shared prompts the whole team can reuse, agreed by RevOps, with credit limits per workflow. It's how a clever one-person prompt becomes a standard the whole revenue team runs on.
Most failed Clay builds start from the tool — a blank table, every field enriched, value that never arrives. We start from a job to be done, build it as a workflow on good data, then layer AI on top.
Take a real job someone does every week — route this lead, research this account, score this list. Not "what can Clay do," but "what job are we trying to finish."
Define what good data looks like for that job and build only the enrichment it needs. Scope the data to the decision, and credits track value instead of curiosity.
With clean, scoped data underneath, Claygent and AI columns do the reasoning — qualify, summarise, draft — on a foundation you trust.
Large organisations start one step earlier — with the business case. Enrichment is both critical and expensive, so use-case one is almost always the same: replace the stack of separate provider contracts with Clay.
Consolidate enrichment into one waterfall — email coverage from ~60% to ~90%, phone numbers from ~40% to 60–70%, on your terms. That's the business case that gets Clay in the door.
Once the tool is in, define each team's job to be done and build the workflow backwards from it — entering a new market or a new product category, finding the right people, setting the foundation to go to market.
Enterprise gives you token-usage control, AI controls, and DPAs with the data partners — the governance a large revenue org needs to run all of this safely.
The same Clay workspace serves four very different teams. What changes is the job at the centre of each build — and the shape is always the same: enrich the data the job needs, then layer AI on top.
Your reps walk into calls cold. Clay assembles the pre-call context — who's on the call, recent news, the account's history — writes it to the CRM and Slack-messages the rep five minutes before the meeting starts.
Turn every win into the next one. The moment a deal closes, Clay finds lookalike accounts, researches and qualifies them, and finds the contacts — then hands a ready-made list straight to an SDR.
Stop letting your best buyers vanish into form-fills. Inbound hits a Clay webhook, gets enriched and de-anonymised, then routed — enterprise to a rep, SMB to nurture — while AI scores fit and drafts the first touch per segment.
A weekly scheduled job that does the account manager's prep for them. Clay pulls product usage, recent calls and account news, then Claygent compiles an account-manager brief for every account — ready before the week starts.
We believe every company is sitting on a moat it rarely uses: its own data. The knowledge from every current customer, everything you've learned about the market you operate in. The advantage isn't more data — it's orchestrating the data you already have, and getting it connected.
Done right, you can answer the questions that actually drive go-to-market: what are your customers doing with your product, how are they benefiting, what's improving? Add signals on top and you have a live picture no competitor can buy. But none of it holds on a messy foundation — so we build it in three steps.
Fix the data first. Trusted, de-duplicated, standardised — the version of good everything else depends on.
Tie first-, second- and third-party data into one account record — product usage, buying committee, signals — all in context.
Then, and only then, automate the real jobs — via workflows and AI — on a foundation your team actually trusts.
That's the system we build with Clay — and you own it when we leave.
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