Forem: edperlman

26 Y Combinator-Backed Robotics Startups in 4 Batches. We Tracked the Signals and Surveyed the Market.

edperlman — Mon, 04 May 2026 10:01:41 +0000

We run a trend tracking engine at Inqvey that monitors real-time activity across GitHub, Y Combinator, academic research, SEC filings, Hacker News, and Stack Overflow. Robotic process automation came back with activity across all six sources.

The trend signals

Y Combinator: 26 startups across 4 batches. One of the highest counts in our tracker.
GitHub: 736 new repos in 30 days, 3.2k stars. The tooling layer is expanding fast.
Academic research: 399 papers, 21.6k citations. One of the deepest research foundations across all 20 trends we track.
SEC filings: 9 corporate disclosures. More than AI agents (3) or workflow automation (7).
Hacker News: 27 stories, 121 points. Discussions focused on real-world applications.
Stack Overflow: 5 questions. Developers hitting real implementation problems.

What the buyers say
We ran an AI-powered survey - ~1,000 simulated B2B SaaS respondents across 5 roles. Validated against Ipsos with ±2-6pp accuracy.

52.6% say they'll adopt within 12 months. Solid intent but cautious compared to cybersecurity (67.4%) or conversational AI (60.2%).
Primary driver: efficiency improvement (39.3%). Not cost reduction (27.7%). Buyers want better, not cheaper.
Top barrier: integration challenges (33.1%). Same pattern across every B2B category we research.
40.9% prefer established large-scale providers. The market wants proven platforms, not experiments.

What this means if you're building
The investor signal is strong. The developer activity is real. But buyers are cautious and trust-driven. If you're a startup entering this space, your case studies and credibility matter as much as your product.
Trend signal breakdown: https://inqvey.com/trends/robotic-process-automation-2026
Full survey results: https://inqvey.com/data/robotic-process-automation-2026

We Asked ~1,000 Engineering Leaders How They Choose Developer Tools. Features Came Second.

edperlman — Sun, 26 Apr 2026 07:26:50 +0000

If you're building developer tools, you're probably spending most of your time on the product. Better features, faster performance, more capabilities.

But when we asked the buyers what actually drives their decision, the answer was something else entirely.

We ran an AI-powered study using Inqvey - ~1,000 simulated B2B SaaS respondents across 5 roles: VP of Engineering, CTO, Senior Software Developer, DevOps Engineer, and Director of Product. No human panel. Validated against Ipsos human panel data with ±2-6pp accuracy.

The buying decision starts with fit, not function
Top factor when purchasing developer tools:

Ease of integration - 33.8%
Feature set - 27.6%
Cost-effectiveness - 19.4%
Vendor reputation - 11.9%
Customer support - 7.3%

A third of buyers care about integration before they even look at what your tool does. Good docs, clean APIs, and a smooth onboarding path aren't nice-to-haves. They're the thing that gets you through the door.

On-premise is a relic
What type of tools do teams prefer?

Cloud-based - 31.1%
Hybrid - 26%
Open-source - 20.4%
Proprietary - 14.9%
On-premise - 7.5%

Cloud and hybrid combined: 57.1%. On-premise: 7.5%. If you're still offering an on-premise-first deployment model, you're building for a market that barely exists.

Open-source at 20.4% is worth noting. It's not the majority, but it's a real segment — and one that often converts to paid tiers.

The evaluation cycle is quarterly
63% of engineering teams review their tooling stack quarterly or more frequently. 24.1% do it monthly.

That means the switching window reopens every 90 days. For new tools, this is an opportunity. For incumbent tools, it's a warning — you're being re-evaluated constantly.

What scares buyers
Top concerns when adopting new tools:

Data security - 30.9%
Integration issues - 27.4%
Cost - 17.8%
Training requirements - 13.4%

Security and integration account for 58.3% of all concerns. If your landing page doesn't address these two within the first scroll, you're losing people before they reach the feature list.

61.2% are ready to adopt within 12 months
The demand is there. 69.1% see developer tools as significant or very significant to their operational efficiency. The market is actively looking.
But they're looking for tools that fit - not tools that impress.

Full data
Full survey results with all 6 questions and methodology:
https://inqvey.com/data/developer-tools-2026

Browse all trends and research: https://inqvey.com/trends

60% of SaaS Pros Say They'll Adopt Conversational AI Within 12 Months. Here's What They Actually Care About.

edperlman — Wed, 15 Apr 2026 11:56:29 +0000

If you're building conversational AI tools, the adoption intent is there. But what the market wants might not be what you think.

We ran an AI-powered study using Inqvey - ~1,000 simulated B2B SaaS respondents across 5 roles including VP of Product, CTO, Director of Customer Success, Solutions Architect, and Customer Support Manager. No human panel. Validated against Ipsos human panel data with ±2-6pp accuracy.

Here's what developers and product teams should pay attention to.

Integration beats intelligence

We asked what feature matters most in a conversational AI solution:

Integration capabilities - 33.7%
Natural language processing - 29.1%
Scalability - 19.6%
Customization - 15.7%

The best NLP in the world doesn't win the deal. Fitting into the buyer's existing stack does. If you're building here and spending all your time on model quality while your integration story is weak, you're solving the wrong problem.

The buying motivation is operational, not strategic
Why are companies considering conversational AI?

Improving customer service - 32.3%
Operational efficiency - 29.6%
Reducing costs - 19.5%
Competitive advantage - 14.3%

Nobody's buying this to differentiate. They're buying it because their support queue is too long and their ops team is stretched. That changes how you position and how you sell.

Data privacy is the wall
34.5% say data privacy and security is their top concern. Integration complexity second at 26.9%. Cost third at 15.2%.

For developers - this means your security posture, compliance certifications, and data handling policies aren't nice-to-haves. They're the first thing the buyer evaluates. Ship the SOC 2 badge before you ship the next feature.

The momentum is real
60.2% say they're likely to adopt within 12 months. 74.1% see conversational AI as transformative. 58.2% say their company's attitude toward AI has become more positive this year.

The demand side is ready. The question is whether the supply side - the tools being built right now - can meet buyers where they are: secure, easy to integrate, and focused on operational pain.

Full data
Full survey results with all the questions and methodology:
https://inqvey.com/data/conversational-ai-2026
Browse all trends and research: https://inqvey.com/trends
Building in the conversational AI space? What's the hardest part - the model, the integrations, or convincing buyers to trust it?

We Asked ~1,000 Simulated SaaS Professionals About Vibe Coding. The Data Challenges a Few Assumptions.

edperlman — Wed, 08 Apr 2026 09:30:34 +0000

Vibe coding keeps showing up in every feed, every newsletter, every conference agenda. We wanted to move past the takes and look at what the market actually thinks.

We ran an AI-powered survey using Inqvey - ~1,000 simulated B2B SaaS respondents across 5 roles: VP of Product, CTO, Director of Customer Success, SaaS Sales Manager, and Implementation Specialist. No human panel. Validated against Ipsos human panel data with ±2-5pp accuracy.

A few things stood out.

The interest is real but cautious

52.9% say they're likely to implement vibe coding. But only 19.7% say very likely. The rest are somewhat likely (33.2%) or sitting on the fence (24.2% neutral). This isn't a stampede. It's a market watching closely and moving carefully.

Integration is the blocker, not price

We asked about the primary barrier:

Technical integration challenges - 31.1%
Uncertain ROI - 22.2%
Lack of skilled personnel - 21.8%
Cost - 20.6%

Developers building for this space should pay attention. The people you're selling to aren't worried about what it costs. They're worried about how it fits into what they already have and whether it actually delivers.

UX first, infrastructure later

What's most appealing about vibe coding?

User experience enhancement - 32.6%
Data-driven customization - 29.1%
Flexibility - 16.6%
Scalability - 15.5%

The market sees vibe coding as a product experience layer. Not a performance optimization. Not a scalability solution. If you're building here, lead with the user experience story.

Nobody has a process for evaluating this

This is the quiet finding that matters most. Only 31.9% do regular reviews of emerging tech like vibe coding. 35.9% say occasional. Almost 20% say ad-hoc.

The interest is ahead of the evaluation capability. That means early movers who make adoption easy - good docs, clear integration path, low switching cost - will win disproportionately. The market wants to try this but doesn't have a structured way to assess it yet.

Full data

Full survey results with all 6 questions and methodology:
https://inqvey.com/data/vibe-coding-2026

Browse all trends and research: https://inqvey.com/trends

Is anyone here building with vibe coding in production? Curious what the integration experience actually looks like.

We Surveyed 300 AI-Generated Respondents on AI in Retail - Here's Where the Market Actually Wants AI

edperlman — Fri, 27 Mar 2026 23:45:27 +0000

If you're building AI products for retail, the question isn't whether the market wants AI. It's where.

We ran an AI-powered survey with 300 AI-generated respondents across 4 AI personas matching B2B retail professionals - CTOs, heads of operations, AI solutions architects, and retail data analysts. No human panel. Validated against Ipsos human panel data with ±2-5pp accuracy.

Here's what the data says.

67.7% say they'll adopt AI within 12 months
27.7% very likely. 40% somewhat likely. The adoption intent is clear. But intent without understanding the barriers is useless if you're building for this market.

The top barrier isn't cost
This is the part most people get wrong. When we asked about the primary concern:

Data security - 31%
Integration complexity - 28%
Cost - 21%
Lack of expertise - 17%
No concerns - 3%

If you're building AI for retail and your pitch leads with ROI and cost savings, you're answering a question that isn't top of mind. The buyers are worried about security and integration first. Price is third.

Inventory management wins by a wide margin
When asked where AI would help most:

Inventory management - 38%
Sales forecasting - 26.3%
Customer service - 20%
Marketing - 13%
None - 2.7%

Retail wants AI in the back end. Inventory, demand forecasting, supply chain. Not chatbots. Not personalization. Not marketing automation. The operational pain is louder than the customer-facing opportunity.

For developers - this is useful signal. The highest-demand use cases are the ones that touch operations, not the ones that touch the customer.

Interest is growing, and so is budget
66% say their interest in AI for retail increased over the past year. 68.3% say they're willing to allocate budget. That's not vague optimism - that's purchase intent.

But only 3% say they have no concerns about implementation. Nearly everyone wants it. Nearly everyone is nervous about something.

What this means if you're building
The market is telling you three things:

Build for the back end first. Inventory and forecasting, not marketing.
Lead with security and integration, not price. Those are the real objections.
The buyers are ready. Budget is allocated. But trust and implementation are the bottlenecks.

Full data
Full survey results with all the questions, persona breakdown, and methodology:
https://inqvey.com/data/ai-retail-2026
We track 20 technology trends and run market research across them:
https://inqvey.com/trends
If you're building for retail - what are you hearing from buyers? Does this match?

YC Funded 8 Workflow Automation Startups in 4 Batches. We Dug Into What GitHub, SEC Filings, and Academic Research Show.

edperlman — Tue, 24 Mar 2026 03:38:37 +0000

Workflow Automation is one of the quietest strong signals in our trend tracker right now. No hype cycle. No headline wars. Just real activity from developers, investors, researchers, and enterprises - all moving at the same time.

We built a trend tracking engine at Inqvey that monitors real-time activity across GitHub, YC, academic research, and SEC filings. We pointed it at Workflow Automation - and the data is worth a look.

YC is funding this heavily

8 startups across the last 4 batches. That's one of the highest counts we're seeing across the 20 trends we track right now. YC doesn't repeat-fund a category unless they see a big market with room for new entrants. 8 companies across 4 consecutive batches is sustained conviction, not a one-off bet.

698 new GitHub repos in 30 days

Developers are building. But here's the thing - only 792 stars across all of them. That's a lot of new tooling with not much traction yet. Most of these projects are early. The space is still wide open for someone to build the thing that gets real adoption.

7 SEC filings

Public companies are disclosing workflow automation as material to their business in regulatory filings. Nobody puts something in a 10-K unless their legal team considers it significant enough to affect financial performance. This has moved past IT budgets into board-level conversations.

183 papers, 97 citations

Moderate academic output compared to something like cybersecurity (396 papers, 9,400 citations). The applied side is ahead of the research side here. This is a practitioner-driven space - people are building and shipping, not waiting for the theory to catch up.

Hacker News: 14 stories, 36 points

Low community buzz relative to the investor and developer activity. Workflow automation doesn't spark the same debates as AI agents or security breaches. But the fact that VCs and developers are active while the community is quiet is actually a useful signal. Less noise, less competition.

What this pattern tells you

High investor conviction. High developer activity. Low community hype. That combination usually means a "boring but big" market. The buyers have real pain, the VCs see it, but there's no media circus driving up competition.

For anyone thinking about building in this space - pain-driven markets with low noise tend to convert faster because the buyer already knows they have a problem.

Full data

We track workflow automation alongside 19 other technology trends, updated regularly. Each one gets a full signal breakdown with sources and evidence.

Browse all current trends: inqvey.com/trends

Full Workflow Automation breakdown: inqvey.com/trends/workflow-automation-2026

What's the most underrated space you're watching right now?

We Tracked 20 Tech Trends Across Real Data Sources. Here's What's Actually Hot Right Now.

edperlman — Sat, 21 Mar 2026 22:00:55 +0000

AI Agents is the strongest signal in our trend tracker right now. Not because someone wrote a hot take about it. Because the data says so.

We built a trend tracking engine at Inqvey that scans real-time data sources to identify what's actually trending in technology. Not opinions. Not vibes. Real, verifiable activity from developers, investors, researchers, and enterprises.

Here's what we found for AI Agents.

Hacker News: 674 stories, 3,678 points

Hacker News is where the tech community discusses what matters. 674 stories about AI Agents in the last 14 days, with 3,678 total upvotes. That's a massive amount of attention from developers and technical founders. HN activity tends to precede mainstream adoption by 1-3 months.

GitHub: 791 new repos, 150,300 stars

791 new repositories created in the last 30 days. Developers aren't just talking about AI Agents, they're building. 150,300 stars across those repos means the projects are getting real traction. GitHub creation velocity is typically a 3-12 month leading indicator of market adoption.

Y Combinator: 25 startups across 4 batches

25 YC-backed companies working on AI Agents, spread across 4 recent batches. When Y Combinator funds 25 startups in a single category, that's serious conviction from the most influential startup accelerator in the world.

Stack Overflow: 8 questions

Relatively low compared to other sources, which tells us something important: developers are building AI Agents but the tooling ecosystem is still maturing. Stack Overflow questions typically pick up as technology moves from experimentation to production deployment.

Academic Research: 291 papers, 2,800 citations

291 papers published on AI Agents recently, with 2,800 citations. Academic research is usually the earliest signal. The fact that researchers are publishing heavily means the theoretical foundation is solid and applied work is accelerating.

SEC Corporate Filings: 3 disclosures

3 mentions in SEC 10-K/10-Q filings. This is the newest signal and the most significant. When public companies disclose a technology to regulators, they consider it material to their business. This number is small now but it's a strong validation signal. For comparison, Generative AI already has hundreds of SEC mentions, and AI Agents is following the same early pattern.

What this convergence means

When developers are building, the community is discussing, investors are betting, researchers are publishing, and enterprises are disclosing all at the same time, that's real market movement, not hype.

This level of convergence historically precedes mainstream adoption within 3-6 months.

The gap that tells a story

The interesting gap is between GitHub activity (791 repos) and SEC filings (3). Developer tooling is way ahead of enterprise adoption. That gap usually closes as the tooling matures. If you're building in the AI Agents space, you're early, and that's a good position.

Compare this to Generative AI, which has the opposite pattern: heavy SEC disclosure but relatively fewer new GitHub repos. Generative AI is enterprise-driven. AI Agents is developer-driven. Both are real, but they'll play out differently.

Full data

We publish the complete source-by-source breakdown for AI Agents and 19 other tech topics, updated regularly.

Browse all current trends: inqvey.com/trends

Full AI Agents breakdown: inqvey.com/trends/ai-agents-2026

What trend are you watching right now?