AutoDoc turned R&D tax credit inbound signups into demo-ready conversations automatically.
AutoDoc AI automates R&D tax credits (SR&ED, §41, UK relief, AU incentive, UAE) by reading engineering tools like Jira and GitHub. Nudgy sits between AutoDoc's lead form submit and the human demo: it calls fast, qualifies the lead's R&D profile on a real conversation, writes clean HubSpot memory, and routes warm leads to the right owner with prep-ready context.
Reached in under 5 min
Qualified as demo-fit
Demo attended
Median speed to first touch
The short version
- AutoDoc had high-intent R&D tax credit inbound leads coming in.
- Manual follow-up was too slow and inconsistent.
- Nudgy called those leads within minutes during their working hours.
- It qualified R&D spend, program (SR&ED, §41…), tooling, and claim deadline.
- HubSpot got clean fields, owner tasks, and transcript summaries automatically.
- More qualified buyers reached the human demo with context and showed up.
A high-intent R&D tax credit inbound funnel that lived or died on speed.
AutoDoc AI runs a public evaluation offer. Every form submit is a finance leader, founder, or accounting partner raising their hand on R&D tax credits. The problem was never demand. It was the gap between submit and demo.
AutoDoc's inbound motion runs through autodocai.io (evaluation offer). Marketing brings R&D-heavy companies and accounting partners in. The form captures intent. From there, conversion depends entirely on how fast and how well that lead gets followed up. These buyers want their R&D context understood, not generically pitched.
AutoDoc didn't need more leads. It needed a faster, more consistent way to handle the ones already coming in across US and Canadian time zones. Nudgy became the first response layer, calling new signups while intent was still fresh, qualifying their R&D profile through voice, and preparing the human owner before the demo.
About AutoDoc AI
AutoDoc AI automates R&D tax credit documentation by reading the tools engineering already uses: Jira, GitHub, docs. It structures eligible R&D activity into audit-ready claims for SR&ED, §41, UK relief, AU incentive, and UAE programs.
category = R&D tax credit automation
programs = SR&ED · §41 · UK · AU · UAE
integrations = Jira · GitHub · docs
buyers = in-house R&D + accounting partners
coverage geo = US + Canada
stack = HubSpot CRM
Inbound demand was real. Follow-up was too manual.
High-intent R&D buyers were cooling between form submit and the human demo. Reps were doing the messy middle by hand, and HubSpot was paying for it.
AutoDoc's BDRs were stuck running the messy middle by hand: chasing callbacks across US and Canadian time zones, taking inconsistent notes, and trying to keep HubSpot honest while new inbound leads kept rolling in.
By the time a human owner finally got the demo, motivation had cooled, qualification depth varied wildly between reps, and marketing was flying blind on what these R&D buyers actually said about their tax program, engineering workflow, and claim deadlines.
Overheard · BDR
“I was on hour three of callbacks and still hadn't reached the finance leaders who came in this morning.”
Overheard · Sales lead
“Every rep qualified differently. We had no consistent capture of R&D spend, tax program, or engineering tooling going into demos.”
Overheard · RevOps
“HubSpot looked fine. The fields underneath had no R&D context, no claim deadline, no Jira / GitHub signal.”
Nudgy became the immediate voice layer between lead form submit and human demo.
For eligible signups, Nudgy runs the same qualification loop before the human demo owner steps in. Seven things happen in the first ~12 minutes after a form is submitted.
Inbound callback architecture · live
T+0 → T+12 MINReads context the moment a lead form is submitted
Pulls lead source, country, tax program (SR&ED, §41, UK, AU, UAE), CRM history, and campaign attribution before the call is placed.
Runs preliminary research on the lead
Builds a mini company brief: industry, R&D footprint, engineering tooling signals, and likely claim profile from public sources.
Calls within minutes
Places the outbound call with autonomous retry policy and fallback SMS + email, scoped to local working hours.
Qualifies on a real conversation
Captures R&D spend range, applicable tax program, current process, tooling (Jira / GitHub / docs), claim deadline, and demo fit.
Reduces no-show risk inside the call
Confirms meeting intent, validates fiscal-year urgency, and primes owner-ready expectations before the demo.
Writes structured memory into HubSpot
Pushes summary, fields, owner tasks, and transcript tags, including claim profile, blocker map, and engineering-tool signals. No rep cleanup needed.
Routes the right specialist into the demo
Hands off to the correct owner (in-house R&D buyer or accounting-firm partner motion) with a prep-ready brief.
None of these steps replace the human demo. They make sure that by the time a human picks up the conversation, the lead is already qualified, the context is already in HubSpot, and the owner already knows what to lead with.
Funnel velocity, stage by stage.
Same demand. Same public offer. Same human demo team. The only thing that changed was the layer between submit and call.
Pilot form submits
Before
100%
After Nudgy
100%
Reached in < 5 min
Before
31%
After Nudgy
92%
Qualified as demo-fit
Before
28%
After Nudgy
54%
Demo attended
Before
17%
After Nudgy
46%
Why no-show drops
Nudgy confirms intent inside the qualification call, validates buying context, and primes the lead for the human demo. Reminder fallbacks and a no-show risk score do the rest.
Why speed matters here
Inbound interest decays fast. Replacing hours of manual response with a 2-minute callback keeps context and motivation fresh when the first conversation starts.
The funnel did not need a new top. It needed a faster, more consistent middle. Once Nudgy was placed there, the same inbound traffic produced more qualified, demo-ready buyers, and more of them actually showed up.
The clearest view of what changed.
One row per part of the operation. Every line is something AutoDoc's team felt the next week.
Speed
Leads waited hours for manual callback across US + Canada time zones.
Nudgy called in minutes, in the lead's local working hours.
Qualification
Scripts varied by rep. R&D spend, program (SR&ED / §41), and tooling were rarely captured.
Consistent capture: R&D spend band, tax program, Jira/GitHub use, claim deadline.
Demo handoff
Owners entered demos cold and had to guess at company R&D context.
Owners receive a prep-ready brief: claim profile + blocker map + tooling notes.
CRM hygiene
Sparse notes, missing R&D context, delayed updates.
Structured fields, claim signals, and owner tasks synced into HubSpot.
Marketing insight
Click data and anecdotal rep summaries.
Transcript themes by program, blocker clusters, and persona language at scale.
Nudgy turned our lead form submissions into immediate, intelligent callback loops. We stopped losing momentum between signup and demo, and our team works from rich, structured context instead of fragmented notes.
Sineth Pathirana
What Nudgy writes into HubSpot after the call.
One real-world record after a single qualification call. The record is generated from the conversation, not from manual rep cleanup.
Lead
Maya Chen · Head of R&D Finance
Northwave Robotics · Toronto, ON
Source
AutoDoc AI · inbound offer
Campaign · sred_q4_inbound · CA
intent_score
tax_program
rd_spend_band
engineering_stack
blocker_taxonomy
claim_deadline
persona_role
no_show_risk
next_recommended_step
owner_task
Task created for Owner · Maya's AE
“Walk through the Jira + GitHub ingestion flow before SR&ED demo. Maya needs proof engineering doesn't change how they work.”
Live transcript extraction
Maya · 03:42
“We run engineering across Jira and GitHub. Our SR&ED process is still 90% manual every year. I need to know AutoDoc can pick up our existing documentation without changing how engineers work.”
Nudgy extracted
tax program
SR&ED · Canada
tooling
Jira + GitHub (in production)
blocker
engineer workflow disruption
next step
send Jira + GitHub ingestion walkthrough
owner prep
lead wants zero-disruption proof for engineering
Same shape on every call. RevOps gets clean, consistent fields ready for routing and reporting. Marketing gets transcript-level language patterns. The AE gets a brief that actually helps them open the demo with context, not guesswork.
From form submit to qualified handoff in ~12 minutes.
The callback loop went live in five days. No platform replacement. No long onboarding. Configuration, mapping, launch.
Lead form submit
T+0Lead completes the AutoDoc inbound form in US or Canada.
Nudgy callback
T+2 minPersonalized opener referencing the lead's likely R&D footprint.
Qualification + memory
T+5 minCaptures R&D spend, tax program, tooling, claim deadline, persona.
Human demo handoff
T+10 minRoutes qualified lead to the right owner for the in-house buyer or partner motion.
HubSpot + analytics sync
T+12 minWrites fields, notes, tasks, transcript tags. Done.
Launched in five days.
Connected AutoDoc inbound form flow + HubSpot objects and owner rules.
Imported R&D-specific qualification rubric, objection taxonomy, territory logic.
Enabled callback policy for US / Canada with local-hours retry constraints.
Activated transcript extraction fields (program, tooling, claim deadline) + RevOps triggers.
Launched live and monitored conversion, no-show, handoff quality.
What Nudgy ran on its own
- · Callback trigger + retry policy
- · Persona-aware conversation sequencing
- · Preliminary lead context enrichment
- · Structured transcript extraction
- · CRM field + task synchronization
- · Marketing intelligence tagging at transcript level
Beyond the conversion lift, three quieter wins compounded.
Beyond the conversion lift, AutoDoc also improved response speed, rep prep time, CRM quality, and marketing visibility.
Speed
2m 14s
Median first human touch
92%
Reached within 5 minutes
Rep efficiency
9.4h
Time saved per SDR / week
−63%
Owner prep time before demo
Data quality
Up to 48
Structured fields per lead
Marketing + RevOps
Transcript themes captured
Speed and trust by default.
AutoDoc's inbound funnel depends on speed and trust. If a lead waits hours, motivation fades. If a human owner enters demo cold, the conversation starts from zero.
Nudgy compresses the gap between signup and qualified handoff by making immediate outreach, structured memory, and prep-ready routing the default, not a stretch goal a BDR has to fight for every Monday.
The human demo did not go away. It got better. Nudgy handles the messy middle between form submit and demo so the owner can enter the room with context instead of guesswork.
Wins by persona
Demand Gen
+31% signup → demo liftFull-funnel signal from real conversations by tax program, geo, and engineering tooling, not just form + click activity.
SDR / AE
−63% prep time per demoWarm, context-rich handoffs with R&D spend band, claim deadline, blocker, and recommended demo framing.
RevOps
Up to 48 fields / leadClean structured fields and consistent writeback, ready for SR&ED / §41 segmentation and routing automation.
Marketing Ops
Theme clusters in CRMTranscript-level language patterns by program (SR&ED, §41, UK, AU, UAE) to power hyper-personalized campaigns.
Answers to the questions buyers usually ask.
What does AutoDoc AI do?
AutoDoc AI automates R&D tax credit claims (SR&ED in Canada, §41 in the US, R&D Relief in the UK, R&D Incentive in Australia, and the UAE R&D credit). It connects to engineering tools like Jira, GitHub, and documentation platforms to surface and structure eligible R&D activities so finance teams and accounting partners can file stronger, faster, audit-ready claims.
Who is the AutoDoc offer for?
Two main buyers: (1) in-house R&D-heavy companies such as software, hardware, biotech, and robotics, where finance and engineering co-own claim quality, and (2) accounting / advisory firms managing SR&ED, §41, or R&D claims for client portfolios.
What changed with Nudgy in this rollout?
AutoDoc replaced lagging manual callback workflows with an always-on AI conversation loop that calls inbound leads quickly, qualifies R&D spend / program / tooling depth, and hands warm prospects to humans with full context.
How does this affect no-show and conversion?
By reducing response delay, increasing conversational personalization, and aligning the next step to each lead's tax program and fiscal-year urgency, AutoDoc saw lower no-show rates and stronger signup-to-demo progression.
How quickly did this go live?
The initial production callback loop went live in five days: HubSpot integration, R&D-specific qualification rules, US + Canada routing logic, transcript extraction fields, and launch monitoring.
What exactly is written into HubSpot?
Nudgy writes intent score, applicable tax program, R&D spend band, engineering stack signals, blocker taxonomy, claim deadline, persona role, no-show risk, next step, owner task, and transcript summary tags.
Run this callback loop on your own funnel.
Nudgy plugs into HubSpot or Salesforce, calls high-intent leads in minutes, qualifies on a real conversation, and writes structured memory back automatically.