Jama Software

For medical device manufacturers, process validation is often associated with the manufacturing floor. That’s not wrong, but successful medical device process validation starts much earlier, well before a manufacturing team begins executing validation activities.

It begins with the requirements, risks, specifications, and design decisions established during product development, as well as how effectively that information makes its way into manufacturing.

Design transfer, while sometimes mistakenly thought of as a regulatory milestone or documentation exercise, is a critical connection point between R&D and manufacturing.

When traceability stops at that handoff, manufacturing teams can be left reconstructing relationships among design outputs, process requirements, specifications, equipment, risks, and validation activities. That can mean lost context, missing traceability, and risks that are harder to identify before production begins.

The more effective approach is to extend traceability beyond R&D and into manufacturing, creating continuity from concept to development, through manufacturing, all the way to the field.

Ready to learn more? Visit our latest blog https://ow.ly/3PwX50ZRb53

Process Validation Starts Earlier Than You Think Learn why medical device process validation starts before manufacturing and how continuous traceability can connect design transfer through production.

The January 2026 Artificial Intelligence Strategy for the Department of War sets a demanding delivery standard. Programs are expected to operate with accountable leaders, aggressive schedules, measurable outcomes, rapid iteration, transition-user demonstrations within six months, and monthly progress reviews. The strategy also calls for cycle-time measurement, rapid model updates, modular interfaces, and faster resolution of barriers involving data, authorizations, test and evaluation, certification, and contracting.

Spec-Driven Development, or SDD, can help fill that gap.

In this article, SDD means using a reviewed and versioned specification as the primary input for implementation. The specification brings together requirements, operational context, interfaces, constraints, and acceptance criteria. Code, tests, and an implementation summary return to the same evidence chain. Learn more

From AI-First Strategy to Fielded Capability: The Case for Spec-Driven Development in Defense Explore how defense software teams can meet aggressive AI delivery goals while maintaining traceability, verification, modularity, and control with SDD.

Jama Connect has once again been named a Leader in the requirements management software G2 category, earning top recognition in G2’s Fall 2026 Grid® Report for Requirements Management. Jama Connect received the highest Satisfaction score in the category, along with recognition across customer relationships, usability, market segments, regions, and momentum.

Jama Connect Named a Leader in G2’s Fall 2026 Requirements Management Report
In the Fall 2026 Grid Report, G2 named Jama Connect a Leader in Requirements Management and awarded it the highest Satisfaction score in the category at 96. Jama Connect also earned a G2 Score of 93, and 96% of users rated the product four or five stars.

The Fall 2026 recognition spans multiple G2 reports and categories:
- Leader: Overall, Enterprise, Mid-Market, and Small Business
- Best Relationship: Overall, Enterprise, and Mid-Market
- Best Usability
- Regional Leader: EMEA and Europe
- Momentum Leader

Engineering organizations rarely choose requirements management software on a single capability. Teams weigh how a solution supports day-to-day users, collaboration across stakeholders, growth from startup to enterprise scale, and long-term adoption. Recognition across so many segments and dimensions signals that Jama Connect performs well against each of those needs, not just one.

Takeaway: Consistent, category-wide G2 recognition gives buyers confidence that Jama Connect delivers value across the full evaluation, from usability to enterprise scalability.

Learn more in today's blog 👉 https://ow.ly/raKS50ZPTZ9

Jama Connect® Recognized as a G2 Leader for Requirements Management Software See why Jama Connect leads requirements management software G2 results in Fall 2026, plus its history of G2 awards and customer reviews.

At Jama Software, we apply Spec-Driven Development (SDD) within our own engineering and product development organizations. We use Jama Connect® and AI engineering workflows internally across our own engineering and product development teams, giving us firsthand insight into how requirements, traceability, verification, and human oversight help turn AI coding speed into product velocity.

As we’ve expanded SDD across real projects, we’ve established a disciplined approach for turning AI coding speed into greater product velocity. Requirements quality, engineering context, human judgment, testing, and traceability all become more important as development accelerates.

In this blog, learn how the approach works in practice and the results we’re seeing 👉 https://ow.ly/VEhq50ZPPJa 

How Jama Software Uses Spec-Driven Development for AI Engineering Workflows See how Jama Software adopted an AI engineering workflow, using Spec-Driven Development, human oversight, and traceability to ship faster.

A requirement changes. How quickly can you see what’s affected downstream?

In our latest Features in Five demo, see how the new Trace View Canvas in Jama Connect® gives teams a visual way to investigate relationships and assess change impact.

With Trace View Canvas, teams can:

- Follow upstream and downstream relationships across multiple levels
- Find gaps in traceability and missing coverage
- Create relationships directly in the canvas
- Move between canvas and grid views without losing their configuration

When requirements change, understanding the full impact shouldn’t require piecing together relationships across disconnected views. Trace View Canvas gives engineers a clearer picture of what’s connected, what needs attention, and where traceability is incomplete.

Watch the demo: https://ow.ly/2N3L50ZMo1r

Trace View Canvas will debut in beta with Jama Connect 9.40 and 9.41.

Traceability Visualization: Jama Connect® Features in Five Uncover the power of visual traceability using the Trace View Canvas in Jama Connect. Enhance your impact analysis today.

A requirement changed six months ago. The test case still points to the old version. The risk assessment was updated, but nobody can tell whether the design team reviewed the change. Now an audit is approaching, and a systems engineer has to reconstruct what happened.

The problem isn't a lack of documentation. The engineering information exists. It just isn't connected. Audit-ready documentation depends on preserving those connections as engineering work happens, rather than reconstructing them when an audit approaches.

Read our latest blog to learn what audit-ready documentation looks like for industrial products
https://ow.ly/91XA50ZLIjJ

Audit-Ready Documentation Starts During Engineering, Not Audit Prep Learn how industrial engineering teams can maintain audit-ready documentation with connected requirements, traceability, baselines, reviews, and verification.

For aerospace and defense programs, scale rarely arrives all at once. Programs grow one supplier, subsystem, and software release at a time. Teams add another product variant. A new verification activity appears after a design review.

Before long, a program that once felt manageable evolves into a highly interconnected system with millions of relationships between requirements, designs, software, tests, risks, and compliance evidence.

At first, none of these changes feel drastic, then engineering teams suddenly find themselves spending more time coordinating work than completing it. Reviews take longer and traceability becomes harder to maintain. Certification preparation becomes a weeks-long event.

At this point, complexity grows faster than the program itself. As complexity grows, so does the effort required to keep the program aligned.

Learn more about the hidden cost of scale, and the challenge that many long-running aerospace and defense programs face, in our recent blog 👉 https://ow.ly/IGCm50ZIvfQ

Why Scale Limits Become a Hidden Cost in Long-Running A&D Programs Achieve engineering scalability and manage operational complexity. Learn to overcome scale limits in long-running aerospace and defense programs.

AI coding agents can move fast. The harder question is whether they’re building from the right requirements.

In this new Features in Five demo, Patrick Knowles shows Spec-Driven Development (SDD) in action using Jama Connect® and Jama Connect MCP.

Watch as approved requirements in Jama Connect become governed context for Codex to generate an implementation plan, tasks, and working code. The process keeps a human in the loop and maintains Live Traceability™ between requirements and implementation.

The demo shows what it looks like to move from requirements to code in minutes without giving up the structure, review, and traceability engineering teams need.

Watch the demo 👉 https://ow.ly/B71n50ZIvb8

From Requirements to Code with SDD and MCP: Jama Connect® Features in Five See spec-driven development in action as approved requirements guide AI-generated plans, tasks, code, validation, and traceability with Jama Connect.

Ask a machine builder, automation supplier, or robotics manufacturer whether their products are safe, and the answer arrives quickly and with confidence.

Ask that same organization to produce, on demand, the complete evidence chain for a single hazard, how it was identified, which safety function mitigates it, what performance level that function achieves, how the function was validated, and against which revision of the design, and the answer takes weeks.

That gap deserves a precise name, because it is routinely misdiagnosed as an engineering problem. It usually is not. The analysis was performed. The testing happened. The engineering judgment was sound.

What the organization has is a compliance evidence gap: the work exists, but the proof of the work is distributed across systems, formats, teams, and calendars, and reassembling it is a project in its own right.

Ready to learn more? Check out our recent blog 👉 https://ow.ly/Zmc150ZIsh1

The model can write the code. It can’t write the safety case.

AI-generated code introduces new security and compliance considerations as engineering teams accelerate software development. Vulnerabilities in the implementation are only one part of the risk. In safety-critical products, teams must establish that generated code reflects approved requirements, accounts for identified hazards and threats, and traces to verification evidence.

That raises a larger question. How do teams gain the speed of AI-generated code without losing the evidence required to justify it?

Learn more in our latest blog 👉 https://ow.ly/hFAP50ZIrc3

AI-Generated Code Risks: Why Safety-Critical Software Needs a Product Context Layer Learn how AI-generated code risks affect safety-critical software and why a product context layer matters for traceability, verification, and compliance.