Chalk Theory LabsWhere insight becomes a shipped engine, not just a deck
Chalk Theory Labs is our applied R&D practice: we turn recurring engagement work into automation, AI-enabled workflows, and operational engines, some kept internal and some built and run as real products.
How ideas become engines
Labs isn't a separate product line. It's what happens when the same problem shows up on a second engagement, and it's faster to rebuild it by hand again.
It starts in an engagement
Every engagement surfaces the same kinds of gaps: a metric nobody's tracking cleanly, a process that's manual because no one's had time to automate it. That repetition is the signal.
We build the fix once, properly
When we catch ourselves solving the same problem twice, we stop and build it as an engine instead of a one-off spreadsheet or slide. Proven internally or on a client's own operation before it's called done.
Sometimes it stays internal. Sometimes it ships.
Most of what Labs builds sharpens how Chalk Theory delivers. Some of it is substantial enough to run as its own product or a client's own operational engine. Prizvox and our farm automation work below are both examples.
Why this isn't just a name
We treat our own engines the way we'd treat a client deliverable. The clearest evidence of that is public: the codebase behind Chalk Theory's own site.
A real CI pipeline
This site itself runs through HTML validation, automated Playwright browser tests across desktop and mobile, dependency auditing, and production link-checking before anything ships. That's the same rigor we'd expect from a client's codebase.A systematic design-token system
Colors, spacing, and typography are defined once as tokens and self-hosted, not scattered across pages by hand. It's the kind of component architecture that keeps a codebase maintainable instead of piling up one-off exceptions.Partners who've built the thing themselves
Jayraj Misra individually brings a process-mining background (using tools like Celonis) and Global Business Services experience from prior work. Ishan Jaggi, who leads Labs, brings enterprise product management experience from Jio Platforms and has personally built and shipped an automation engine for a client before joining Chalk Theory. That's a direct, individually-earned reason a consulting-led team also builds internal tooling rather than only writing about it.What We've Shipped
Two examples of Labs work that went past internal tooling: one a live product we operate ourselves, one an operational engine built for a client.
Prizvox
An SEO, AEO, and GEO audit platform for agencies and consultants.
Challenge: Agencies auditing a client's search visibility had no single tool that covered classic SEO, answer-engine optimization, and generative-engine (AI chat search) visibility together, just a pile of disconnected point tools.
Solution: Built and operate Prizvox end-to-end: multi-provider AI visibility scoring, technical SEO audits, and agency-ready reporting, run as a real subscription product with paid billing.
Farm Operations Automation
An operational automation platform for a poultry farm client.
Challenge: Feeding schedules, environmental monitoring, and production reporting were tracked by hand across separate logs, so issues surfaced late and inconsistently.
Solution: Built an integrated platform connecting feeding schedules, environmental monitoring, and production dashboards, with notifications so staff see an issue the same day it happens instead of at the next manual check.
Outcome: Less manual logging, more consistent monitoring, and faster visibility into problems than the paper-and-spreadsheet process it replaced.
Part of one practice
Labs doesn't stand apart from the rest of Chalk Theory. The engagement work comes from core consulting engagements; the tools we build get the same craft standard as Chalk Studio's design work. Three pillars, one way of working.
If you're evaluating Chalk Theory for GTM or RevOps work, start with our core services →
Have a process you keep fixing by hand?
Tell us what it is. If we've seen it before, there's a good chance we've already started tooling it.