InteliG vs Waydev: From Work Analytics to Execution Intelligence

I watched Waydev’s founder describe his platform recently. Eight years in, YC-backed, enterprise customers. He talked about 150 metrics, cycle time prediction, AI adoption measurement, and customization for each customer.

It is a solid developer analytics platform. But everything he described is still answering the same question the category has asked for a decade: “How productive are my developers?”

Nobody in leadership is actually asking that. They are asking: “Are we building the right things, and is it worth what we are paying?”

Waydev cannot answer that. InteliG can.

What Waydev Does

Waydev sits in the developer productivity category. It pulls data from Git, connects to project management tools like Jira and Azure DevOps, and generates reports on developer activity. Sprint velocity. Cycle time. DORA metrics. Work patterns across teams. They claim 150 metrics and 36 months of historical data.

Their AI play is predictability — feed historical cycle times into an LLM and predict future performance. “Your cycle time is 5 days. We predict you can get it to 3 days and 5 hours.” They also measure AI tool adoption: which teams use Copilot, Claude, ChatGPT.

It is built for VPs of Engineering and engineering managers who want visibility into team productivity. For that narrow use case, it works. You get charts. You get predictions. You get a sense of who is busy.

The problem is that “busy” and “valuable” are not the same thing. And “adopted AI tools” is not the same as “AI is actually changing your output.”

The Analytics Trap

Developer analytics tools share a fundamental flaw: they measure output without connecting it to outcomes. They can tell you that your team merged 47 pull requests last sprint. They cannot tell you whether those pull requests moved the business forward.

Waydev compounds this by depending on project management tools for context. The metrics are only as good as your Jira hygiene. And if you have ever worked at a company where Jira tickets are accurate and up to date, you have worked at a company that does not exist.

Their AI prediction feature sounds impressive until you realize what it is actually doing: predicting that a number will go down if you follow generic advice. That is trend extrapolation dressed up as intelligence. Knowing your cycle time could drop to 3 days means nothing if the code shipping in 3 days is building the wrong thing.

DORA metrics tell you how efficiently your pipeline operates. They do not tell you whether the pipeline is pointed in the right direction.

What InteliG Does Differently

InteliG is not a developer analytics tool. It is an execution intelligence platform built on a fundamentally different premise: Git is the source of truth, and intelligence means connecting engineering work to strategy, finance, and organizational knowledge.

Git as truth, not tickets. InteliG reads your commit history, pull requests, and deployments directly. No dependency on Jira. No ticket hygiene required. The code tells the story — what was built, who built it, and when it shipped. If it is not in Git, it did not happen.

Strategy layer. InteliG tracks declared initiatives and maps commits to strategic objectives automatically. You can see whether your team’s actual work aligns with what leadership said mattered this quarter. Not based on ticket labels someone forgot to update. Based on the code itself. When 60% of your engineering effort is going to an initiative nobody declared, InteliG surfaces that. Waydev cannot — it does not know what your initiatives are.

Finance layer. Every contributor has a cost. InteliG connects engineering output to financial reality — ROI grades per contributor (A through F), cost per initiative, resource allocation against strategic priorities. When the board asks whether the engineering budget is well spent, you have an answer backed by data instead of a slide deck backed by optimism.

Knowledge layer. Decisions happen in meetings, Slack threads, and hallway conversations. They disappear. InteliG preserves decision context and links it to the code it influenced. Action items from sprint planning auto-close when the corresponding code ships. No manual tracking.

AI intelligence, not just AI measurement. This is where the gap is widest. Waydev measures which teams adopted AI tools. InteliG classifies every single commit for AI assistance level — not just “was AI used” but whether it was PRIMARY (AI doing the heavy lifting on code generation) or supplementary. It identifies which AI tool was used, adjusts story points to reflect actual human effort vs AI effort, and surfaces the real implications.

Ask InteliG “How much of our code is AI-assisted?” and Cognis returns: 315 out of 400 commits are AI-assisted (78.75%). The AI assistance level on every high-risk commit is PRIMARY. AI is absorbing 35-65% of effort depending on complexity. One engineer owns 92-100% of commits across every active repository, heavily leveraging AI as a force multiplier — creating a concentration risk that collapses if that person or their AI tooling becomes unavailable.

That is not adoption measurement. That is intelligence. Waydev tells you who uses Copilot. InteliG tells you what happens to your engineering output if Copilot goes down.

Cognis AI reasoning. Cognis is not a chatbot bolted onto a dashboard. It is a reasoning engine that synthesizes across all pillars — code intelligence, strategy, finance, and knowledge — to answer questions no metric can. “Why did velocity drop last month?” might surface a strategic misalignment, a key contributor reassignment, or a decision made in a meeting three weeks ago that redirected half the team. Cognis connects those dots and gives you a specific recommendation.

The Real Comparison

Waydev answers: “How productive are my developers? Which teams adopted AI tools?”

InteliG answers: “Is my engineering organization building what matters, is it worth what I am paying, and what happens when the AI-assisted workflow that produces 78% of my code breaks?”

One is a reporting tool for engineering managers who want prettier dashboards. The other is an execution intelligence platform for engineering leaders who are accountable for outcomes, not activity.

Waydev has 150 metrics and 8 years of history. InteliG has four connected pillars and a reasoning engine that thinks across all of them. Metrics measure the past. Execution intelligence tells you what to do about the future.

Connect GitHub and ask Cognis →