How we deliver / AgenticStack

AI does the routine. The judgment stays human.

AgenticStack is our delivery engine — it turns the whole delivery lifecycle into an agentic pipeline, with a named human accountable at every gate. It makes experienced people faster and more aware, and frees them for the calls that need a human — it elevates them, it doesn't replace them. It's the engine inside Engram's Build.

Our Approach

We treat the entire SDLC as a conversational, agent-run pipeline — requirement, plan, design, stories, implementation, review — with a human signature required at every gate. Architecture, security and compliance decisions are never automated away. It runs inside your own repository as conversation and artifacts, not another dashboard to maintain.

AgenticStack
Capabilities

What we bring. All of it shipped.

01

Requirement → Plan

An agent turns the requirement into a plan you can argue with — scope, risks and open questions — before anyone writes code.

02

Architecture & Design

Design proposed with the trade-offs stated, then reviewed and signed off by an experienced architect.

03

Story Slicing & Estimation

Work broken into stories small enough to review honestly, with estimates that hold up.

04

Implementation, Story by Story

Agents implement one story at a time against the agreed design, so every change stays reviewable.

05

Parallel Code Review

Several reviewers run at once — correctness, security, performance — before a human makes the call.

06

Governance & Human Gates

AI takes the routine; the judgment stays human. A named human signs off at every gate — faster and more aware, never replaced or bypassed.

Featured practice

Not one copilot — a team of specialist agents.

Requirements and solution architects, an implementer, parallel backend / frontend / infrastructure reviewers, and QA — each a specialist with one job, coordinated through artifacts in your repo. Governance rules and domain guardrails are briefed into every agent the moment it spawns, so consistency and compliance hold without enforcement overhead.

Tool-agnostic · bring your model
ClaudeGPT-5GeminiGrokLlamaMistral+ whatever ships next
Case study

Proven on our own healthcare platform.

We run an agentic SDLC on a PHI-bound healthcare build — requirement-to-review with human approval gates, and guardrails (PHI protection, tenant isolation, module boundaries) briefed into every agent. Cost, velocity and status are captured per feature from day one.

Value compounds with adoption — not a Day-1 big bang.

One developer pilots, then four, then the team. We instrument cost, velocity and risk from the start, so leadership sees status without asking. AI will not differentiate companies — workflow architecture will; the organisations that redesign now build at a structural advantage.

Let's build

Build something Real

30 minutes. No pitch deck. A real conversation about your challenge.