Services

We'd rather give you the honest answer than the profitable one. Every service below starts from that.

How we engage

Three modes, used individually or woven together as the work demands.

01
Think with us

Short, opinionated conversations backed by experience. Clear points of view on where AI earns its keep and where it does not.

02
Build with us

Working with your stakeholders on 0 → 1 to prove an idea and get it to where your team can carry it forward.

03
Teach with us

Workshops, patterns and rituals. When we step out of an engagement, the AI-native way of working stays with your team.

What you can call us for

Four audiences inside your company. Different problems, same operating principle: the shortest path to real value.

For Leaders
Honest thinking partner

On strategy, build vs buy, and roadmap calls. Clear points of view backed by experience, not slideware. And we'll tell you when the right answer is "don't do it."

Working prototype as a sounding board

When an idea needs pressure-testing before a decision, we can usually stand up something clickable in a day or two. It turns abstract debates into something real.

AI-native leadership workshops

Focused sessions that start with the leader's own day-to-day work. Not an intro lecture. A working space where leaders learn to let AI quietly handle the noise so they can spend their energy on the decisions that matter.

For Engineers
AI-native engineering processes

Setting up AI-native ways of working around tools like Claude Code and Codex: spec-driven and test-driven development, AI-assisted code review, and agentic skills that quietly automate the redundant work in your engineers' day-to-day.

Building AI and agentic features in your apps

Hands-on with your engineers on the craft side of AI engineering: agent design, orchestration patterns, tool use and function calling, memory and state, prompting for production, and the shift from writing deterministic code to shaping systems that think.

For Products
Prototype → production AI features

Where to place guardrails, how to balance cost against latency, when a smaller model is the right call, and where AI should not go at all. Hard-won lessons from production, including the mistakes we've watched others make.

Choosing the right building blocks

Build vs buy across models, vector stores, agent frameworks, and orchestration platforms. We've made these calls before, and know which ones age badly.

Rebuilding how product gets built

Sprints, backlogs, and planning rhythms reworked so the whole team ships AI-natively, not a traditional team with AI tools bolted on.

For Operations-Heavy Teams
AI triage for manual workflows

A clear-eyed look at where your team is spending time on repetitive, rules-based work that AI can quietly absorb. We map the work before we recommend anything, and we will tell you when the answer is to leave it alone.

Thin-layer automation, not a platform overhaul

Most operational wins do not require a year-long build. We find where a simple AI layer on your existing tools, whether that is document extraction, invoice matching, or reconciliation checks, gets you the majority of the value at a fraction of the cost.

Accountability-first AI design

In regulated environments, someone is always liable. We help you draw the right line between what AI handles and what a person signs off on, so your team moves faster without taking on risk they should not be carrying.

Want to talk about what you're working on?

Tell us where you are and what you're trying to do. We'll be honest about whether we can help. Reach us at hello[at]pathkey.in. And if you're in Pune or Bengaluru, we'd love to do this over coffee.