Code Migration + Refactors
- - Language migrations
- - Version upgrades
- - Codebase restructuring
HOW WE WORK
Higher output, not headcount
We embrace AI across our own workflows and help you do the same. From strategy to implementation.
Why this matters now
Using AI is no longer an advantage.
It's the ability to operationalize it.
Most teams can access the same models. The performance gap comes from the systems around them.
The teams that pull ahead make AI execution intuitive and scalable across the organization
One-off prompts give isolated wins. Systems give durable leverage
Automated workflows learn, expand, and improve with use
Real transformation happens when entire teams buy in
Models get better. The advantage lies in the system you built around it
AI · AI Transformation
Build your edge with AI
We identify where to implement AI to drive real efficiency and ROI.
- AI solutions across product, eng, ops, and sales
- Custom systems built for your specific constraints
- Workflows designed to compound over time
- Performance tracked and optimized continuously
How most orgs use AI
Common gaps we see before a transformation engagement
01
Individual tools, no shared playbook
02
Pilots that never reach production
03
AI bolted on top of broken processes
04
No defined KPIs, no measured outcomes
Where we look first
You could be saving time and resources, we find out where
We drive gains across four core areas where AI creates measurable leverage.
Free up PM time by automating implementation specs, bug reports, and roadmap updates.
Spec throughput
Spec workflows that cut cycle times and improve quality
Feedback loops
Triage and address feedback around the clock
Knowledge store
Understand the source of truth, always
Common questions
Tools are only one layer. We align software, process, and adoption so AI changes operating speed, not just tooling preferences.
Yes. We often run transformation programs across product, engineering, operations, and sales with shared KPIs and governance.
A diagnostic baseline, prioritized roadmap, and initial implementation wins that prove where AI creates measurable business lift.
Yes. We design around your current stack and workflows so adoption is practical and compounding rather than disruptive.
We define KPIs upfront and track outcomes like cycle time, throughput, error rates, and revenue efficiency throughout implementation.
Cognition × Scope
More output.
Same team.
We deploy and operationalize Devin inside engineering orgs—with the workflow design, codebase prep, and governance to make it stick.
- Devin completes tickets end-to-end, asynchronously
- Engineering workflows rebuilt around AI leverage
- Output per engineer increases measurably
- Performance tracked against defined KPIs
# frontendFrontend discussions, UI updates & imple…
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Today
S
Silas2:50 PM
@Devin can you make the knowledge fields always editable?
Devin2:50 PM
@Silas of course! Creating a session and making the changes. See here.
BIS
Can you
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▶The technology
Devin, by Cognition
An autonomous coding agent that researches, plans, and completes tickets end-to-end without constant supervision.
The implementer
Scope
A team of product and engineering experts who’ve used Devin in production to develop a proven, results-driven playbook.
The Cognition Platform
Every Cognition product is powered by the same shared intelligence
SHARED Intelligence
Codebase UnderstandingBusiness LogicMemory & ContextPlanning & Execution
Devin Agent
Cloud-Based & Async
+ moreThe unique platform approach drives compounding ROI & efficiency at scale
AI assistance across the full development life cycle
Understanding Code
Chats with humans about the codebase to aid understanding
Planning a Change
Auto-generates documentation at 50M-LOC scale
Reviewing
Analyzes and fixes complex PRs using codebase-aware context
Testing & QA
Writes 90–100% of tests using playbooks from a human
What we saw internally
With an optimized codebase, Devin unlocks faster shipping, higher quality, and a smaller backlog
Bugs and Backlog Work
- - Ticket resolution
- - CI/CD
- - First-draft PR creation for backlog tasks
Data Engineering + Analysis
- - Data warehouse migrations
- - ETL development
- - Data cleaning and preprocessing
Application Development
- - Frontend bugs and edge cases
- - Unit and E2E testing
- - Building SaaS integrations
Devin works with hundreds of tools
GitHub & GitLab
Devin can independently create PRs, respond to PR comments, and review PRs
Linear & Jira
Assign Devin tickets directly in Linear, or add the Devin tag.
Slack & Teams
@Devin in Slack or Teams to assign tasks. Devin keeps you updated in replies.
Seamless Transition
Bring your existing workflows, pick your models
We make it easy for teams using tools like Claude Code or Cursor to bring their workflows over instantly.
Claude
Cursor
.rulesMCPsagents.mdskillsTask Graphs
Where most orgs are
Common gaps we see before a Devin implementation
01
AI usage is individual and uncoordinated
02
No playbook, no policy, no governance
03
Codebases aren't structured for AI agents
04
Results are inconsistent and unmeasured
What Scope delivers
We make your codebase Devin-ready so every session delivers real output
Devin is powerful out of the box—but the teams seeing the biggest gains are the ones whose codebases, workflows, and guardrails are purpose-built for agentic engineering. That's what we do.
Codebase Report Card
Types
38%
Tests
28%
Docs
30%
Modularity
44%
CI
58%
Agent Readiness
20%
01
Codebase Review
We audit your repos for complexity, ambiguity, and patterns that trip up AI agents
02
Define Guardrails
Policy controls, review gates, and scoping rules so Devin operates within boundaries your team sets
03
Targeted Refactors
Improved type coverage and standardized patterns so Devin can navigate and contribute with higher accuracy
04
Self-Improving Code
Custom conventions, automated linting, and feedback loops that make the codebase easier for Devin and your team
Security & Privacy
Enterprise-grade security & privacy
With Devin, your data is saved within your controlled environment and is never used for training.
- Deploy in a dedicated virtual private cloud (VPC)
- All inputs and outputs are your intellectual property
- SOC 2 Type 2 compliance
- Audit logs and fine-grained access controls
- Integration with custom identity providers (IdP)
Cognition Trust Center
Learn more about Devin's security practices, certifications, and compliance posture.
Common questions
No. It is best for teams with structured ticketing and active delivery workflows, typically five or more engineers.
Yes. We integrate with your current issue tracking, code review, CI/CD, and communication workflows.
We implement policy controls, auditability, and human review gates so outputs stay aligned with quality and security requirements.
Most teams begin seeing early efficiency and throughput improvements during rollout, with larger gains compounding through optimization.
We continue with optimization sprints focused on performance tuning, backlog reduction, and sustained KPI improvement.