Your Company's
Principal Engineering Agent
Identify Hidden Flaws At Design Time. Save Months Of Development Rework.
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The Only Agent With Full Context From Design To Production
1. Business Context
2. Source Code
3. Runtime Infrastructure
Security
Your Data Doesn't Leave Your Company At Any Point. Period.
CentralAgent is hosted in your private cloud and uses your provided AI model:
Coding agents are the
Junior Engineer
CentralAgent is the
Principal Engineer
CentralAgent Does Not Write Code, It Autonomously Stays On Top Of Your Tribal Knowledge To
Identify Hidden flaws at design time
Saves months of post-implementation rework by having CentralAgent review design docs and tickets before they are picked up for development
Cut spec-driven development time by half
Does the heavy lifting at design time by identifying customers, SLAs, existing design patterns, and more.
Understand the business intent
Keeps track of every software task's development cycle from design to production
Review PRs with understanding of the business intent and runtime behavior
Reviews the pull request like a principal engineer who has been tracking the ticket since design time and ensures that the design requirements are met
The Later Flaws Are Discovered, The Order Of Magnitude More Expensive To Fix
Relative cost by escaped defect
Estimate ROI
View full pricing →CentralAgent In Action
Integrate with an API
- Your team owns a database table called
orders - And you'd like to add a column
region_id - The values of this column will be populated by calling another team's API endpoint
xxxxxx/get-regionid-from-orderid
Asks Questions and Identifies risks at design time.
To prevent costly mistakes later, CentralAgent asks critical, often-overlooked questions directly on the ticket.
/get-order-region-id.- What downstream services could be impacted by this change?
- Will this change impact our Service Level Agreements (SLAs)?
- Can we follow existing patterns to avoid reinventing the wheel?
- Is this a historically risky area of the codebase?
Autonomously Researches & Gathers Context
CentralAgent doesn't wait for humans to answer these questions. It branches out autonomously, integrating with your existing tools to investigate each assumption in parallel.
/get-order-region-id.- What downstream services could be impacted by this change?
- Will this change impact our Service Level Agreements (SLAs)?
- Can we follow existing patterns to avoid reinventing the wheel?
- Is this a historically risky area of the codebase?
Synthesizing Findings Into Your Issue Tracker
After roughly two minutes of background research, CentralAgent synthesizes its findings. It compiles the impacted stakeholders, relevant SLA contracts, recommended code patterns, and historical risk assessments, posting them directly into the issue tracker ticket.
Now, your engineers & their coding agents have full, enriched context before they start building.
/get-order-region-id.- What downstream services could be impacted by this change?
- Will this change impact our Service Level Agreements (SLAs)?
- Can we follow existing patterns to avoid reinventing the wheel?
- Is this a historically risky area of the codebase?
- Impacted Customers: 4 premium tenants identified.
- SLA Risk: High. The API latency (p95 250ms) violates the 200ms contract.
- Recommendation: Use the parallel batching Lambda pattern introduced in PR-8922.
- Risk Level: Medium. Modified files have no recent hotfixes.
Reviews PR with business intent and an understanding of runtime behavior.
CentralAgent tracks the project and returns at the Pull Request (PR) stage. Because it has been tracking the software task since the design phase, it reviews the final code to ensure it meets the acceptance criteria and successfully handles the hidden assumptions and risks identified on day one.
Add region_id to orders #9012
This implementation misses the parallel Lambda handler we agreed on in the ticket to maintain the 300ms SLA. Please batch the API calls natively using the existing pattern from PR-8922.