Airbyte began in 2020 as an open-source data integration project that grew into a platform trusted by companies like Rakuten, Mercury, and Perplexity, with a community of 27,000 developers. The AI era opened another opportunity: a new product that helps teams give AI agents the context they need.
That expansion brought a more demanding go-to-market challenge: reaching new buyers while continuing to grow existing products.
Airbyte now runs three core product lines through Octave, each with its own ICP, qualifying logic, and sales playbooks, all in one dynamic context layer.
Octave helps the team understand buyer needs and deliver relevant messaging to each buyer, with all GTM channels working in sync. It powers:
- Qualification for accounts and leads across the products, using product telemetry, nuanced business attributes like seasonality, and more
- Sales enablement in Claude and rep portals
- Personalized content creation
- Ad targeting
- Leadership strategy and market insights
- New hire onboarding
Octave learns from Airbyte’s Gong calls, Salesforce deal data, and BigQuery data to understand buyers’ evolving needs, motivations, and competitive considerations. Then it pushes messaging context and qualification into Claude, Common Room, Instantly, Nooks, Clay, Vector, and other GTM tools. Findings from buyer conversations sync back to Airbyte’s BigQuery warehouse.
The result? More pipeline per rep, qualification-informed ad targeting, and faster time-to-market for their new AI product.
“We've seen a 50% to 100% increase in pipeline per BDR since using Octave.”
Strategy
Leadership turns customer evidence into strategic guidance
The Octave MCP brings company context and intelligence into Claude, where Mario Moscatiello, Airbyte’s VP of Marketing, and his team use it for strategic work:
- Iterate on playbooks
- Refine qualifying agents
- Rewrite positioning
- Analyze pipeline
They also use the MCP for one-off context updates. When a new feature ships or a product's positioning changes, they can simply chat with Claude.
Octave also analyzes buyer conversations and market trends to suggest changes to context automatically.
For example, in one two-week stretch, more than 20 buyer conversations in Gong surfaced concerns about a specific competitor’s unpredictable usage-based pricing model.
Octave recognized the pattern, determined Airbyte’s relative pricing strengths, and suggested an update to that competitor's entity in Octave, so future rep guidance and content would reflect it.
“The beauty of Octave is how easy it is to update. When we refined our new product positioning, we were able to revamp our playbooks and product entity in 15 minutes.”
Qualification
Inferring fit for complex ICPs
Airbyte uses Octave’s Managed Agents to qualify people and accounts across three products. This produces scores and messaging used in Salesforce, Common Room, and a centralized sales rep portal — including recommendations for which sales playbook to use.
Mario and his team built a data spine in BigQuery that feeds Octave’s qualifying agents, with 96 enrichment columns for more than 100,000 accounts. It syncs through Supabase so Octave always has fresh context when it scores.
In addition to classic firmographics, the qualifying agent analyzes:
- Nine dbt models detect seven product signals: connection velocity, CDC activation, credit spikes, multi-user growth, workspace expansion, trial starts, and open-source activity.
- CRM history
- Activity signals from Airbyte’s website and Common Room
- Technographics
- Deep research via the qualifying agent at runtime, including company news, feature launches, blog posts, and job postings
Account-level agents run parallel qualifying logic that scores fit for each of their three products. Person-level agents qualify leads into the best-fit product (out of three), the best-fit sales playbook (out of seven), and the best-fit persona (out of five, like Data Engineer versus AI/ML Engineer).
“Our scoring is good because we give the agent much more context than most teams do, and Octave weighs it all.
The ability to handle all our first-party data is a big differentiator over generic enrichment and qualification tools. We can infer someone’s use case and what really matters to them.”
Airbyte’s ICP definitions are complex. They couldn’t just score with +/- 5 points based on industry and size. Octave’s agents let them understand a company’s business — including nuanced characteristics, like seasonality — then infer fit for each of Airbyte’s products.
They validated person-level qualification on roughly 1,700 signups for the Agents product. Scores and recommended messaging flow into Vector.co for ad targeting, as well as the CRM, Common Room, and internal BDR destinations.
Sales
Helping reps build more pipeline with relevant outreach
Octave sits at the heart of a sales engine that has increased pipeline per BDR by 50% to 100% through better lead prioritization and outreach personalization.
A centralized BDR system runs on a Trigger.dev pipeline. It detects signals, sends leads and accounts to Octave for scoring, routes based on score, and pushes to sequences in Instantly and other tools. Personalized emails and call scripts are ready to go.
“We can now book double the pipeline of an average BDR organization. Without Octave, we would have had to build an insane amount of infrastructure and stitch together 20 Clay tables just to get to the same level of work.”
Each lead’s outreach reflects the use case and messaging angle identified during qualification. Reps focus on Tier 1 leads and can add their own context, while the rest receive automated nurture.
This has dropped research and writing time from 60% to 20% of a BDR’s day. Mario says, “Reps used to take hours to research enterprise and midmarket accounts. This has dropped to 30 or 45 minutes with Claude and ChatGPT. But with Octave, it’s virtually zero.”
The same foundation also supports event-list qualification, lifecycle campaigns, content marketing, and new-hire enablement.
Read more on The GTM Engineer: How Airbyte doubled SDR booking rates
BDRs can chat with Claude for one-offs, like quickly scoring 10 accounts or writing a personalized message to a lead they met at an event. The Octave MCP pulls current data from Salesforce, qualifying logic, and the context graph — empowering reps with the context and guardrails they need to operate independently.
“Octave started spreading within our organization when the MCP launched. My reps are way more independent now, because we’ve taught Octave our strategy.”
Airbyte had tried a range of AI writing tools, but the copy wasn't differentiated enough. With Octave, outreach reflected Airbyte’s positioning and each buyer’s needs.
“We tried every agent researcher under the sun, from Clay agents built on ChatGPT and Claude to Common Room. But the copy looked the same, because they weren’t yet grounded in Airbyte company context — who we are, what we do, what our ICP is, and how we differentiate from competitors.”
“The relevancy of our emails has gone up, so our email reply rates have gone up,” says Mario. “When our reps are having conversations with prospects, prospects are genuinely happy about how relevant the conversation is. That’s why we have a super high pickup rate and conversion to meeting rate on the phone – because we’re talking about the right thing with Octave’s context.”
Paid media
Teaching paid media what a high-fit buyer looks like
Octave’s qualification also guides ad targeting. Airbyte pushes scores into Vector.co and its paid media agency’s BigQuery project, so advertising audiences can reflect the same prioritization as other channels.
A compounding loop improves ad platform targeting over time. The team feeds Octave’s high-scoring contacts back to Google, Meta, and LinkedIn as offline conversions. Rather than just sending a “signed up” lead as a conversion event, which optimizes the ad algorithm for volume, they send leads who have “signed up and scored as high-fit in Octave.”
This teaches the algorithms what Airbyte’s ICP looks like, and how to find more people like them, as the business evolves.
The better Octave gets at scoring, the smarter the ad platforms get at targeting.
A GTM foundation that learns with the business
Airbyte's story has always been about moving data to wherever it creates value — first for analytics, now for AI. Its go-to-market runs on the same principle.
By making its messaging, ICPs, and competitive knowledge a living system in Octave rather than static documents, Airbyte turns institutional knowledge into something every tool, agent, and teammate can act on.
