Giga Reviews & Product Details

At NPC Global we deal with a steady stream of retailer questions around order tracking, delivery windows for shipping supplies, and material availability across our network of facilities. What stands out with Giga is how cleanly the agents connect those conversations to the systems we already use and then complete the next action confirming a shipment, noting a delay, or arranging a replacement without forcing the customer to wait or repeat details. The voice channel in particular feels responsive and natural for our team’s volume. Review collected by and hosted on G2.com.

The initial configuration of certain edge-case policies (for example, multi-facility inventory checks or specific carrier exception rules) required more iterative testing than we expected. Once those were locked in the agents performed well, but the early setup phase could be smoother for teams with highly customized logistics workflows. Review collected by and hosted on G2.com.

Giga’s biggest strength is that it goes beyond basic chatbot-style support. I like that the AI agents can actually handle complex customer issues and workflows across voice and chat, while using company knowledge and policies to keep responses grounded. The continuous improvement around metrics like resolution rate is also useful because it makes the impact easier to measure rather than just tracking chatbot usage. Review collected by and hosted on G2.com.

The main downside for me is that Giga feels more geared toward large, complex enterprise support environments, so it can be more than necessary for simpler use cases. The custom enterprise pricing and implementation requirements can also make it harder to evaluate quickly. I’d also want stronger validation around edge cases because transcript quality, incomplete customer context, and AI-generated root-cause suggestions can affect the reliability of its insights. Review collected by and hosted on G2.com.

I work in customer support operations, where customers often start in chat or email and then later call in. What I appreciate most is the continuity: the context from an earlier interaction carries forward, so the AI agent—or the human who takes over—doesn’t have to start from scratch. The voice experience feels fast enough for a real conversation, and the system is designed to actually complete the request (status checks, simple account changes, and clear next steps), rather than just sending a polite holding message. Review collected by and hosted on G2.com.

Odd or policy-heavy situations still need clear, tight rules and a clean handoff. When escalation criteria are vague, people get bounced around or the agent stops short of what’s needed. It’s worth investing in those definitions early, instead of discovering the gaps once you’re already in production. Review collected by and hosted on G2.com.

The live operational visibility and the continuous improvement loop. On any given day we can see 24 of our 27 agents active, resolving over 12,800 conversations in a 24-hour window at 94.3 % fully automated, with average CSAT at 4.8 and handle time down to 42 seconds. The voice agents in particular (Billing and Tech Support) consistently hit 96 %+ resolution with near-human quality. Being able to set a KPI and watch the system iterate toward it without constant manual tuning is the biggest differentiator. Review collected by and hosted on G2.com.

Initial mapping of some of our more specialized capital-markets workflows and audit/compliance requirements took extra configuration effort. Once live the platform has been stable and the agents continue to improve, but the early setup phase for regulated-data access and custom reporting fields required more back-and-forth than a simpler use case would. Advanced attribution of conversations by specific product line could also be richer out of the box. Review collected by and hosted on G2.com.

The agents improve against the exact KPIs we set instead of staying locked at their initial performance. Once we defined resolution rate as the primary goal, Scout began iterating and the numbers moved in a measurable way without constant prompt rewriting. The voice latency is consistently low and the agents handle interruptions naturally, which makes longer, multi-party conversations feel smoother than other tools we tested. Review collected by and hosted on G2.com.

Very edge-case or highly customized policy scenarios still require extra testing and tighter guardrails before full autonomy. We spent additional time in the early weeks validating those specific workflows. The platform itself is capable, but the initial configuration effort for those outlier cases is higher than for standard FAQs. Review collected by and hosted on G2.com.

I like how Giga handles routine customer conversations without constant agent involvement. It quickly responds to common requests, which helps reduce repetitive work. This gives the support team more time to focus on customers who need personal attention. I also appreciate how consistently Giga manages routine requests and keeps the conversations moving smoothly without requiring an agent for every step. Review collected by and hosted on G2.com.

One area that could be improved is how Giga handles more complex and unusual customer requests. Sometimes the AI may need additional context or a human agent to step in, so better handling of edge cases is needed. I'd like Giga to handle multi-step requests with more context from the customer's previous interactions and account history. It would also help to have clearer confidence signals and an automatic handoff to a human when the AI is unsure, so customers don't have to repeat the same information. Review collected by and hosted on G2.com.

What I like most about Giga is how straightforward it feels to use. I don’t have to spend much time figuring out where everything is or how the different features work. It also helps me get things done more quickly, which is probably the biggest advantage for me. For me, the value is fairly good compared with what I’m paying. I mainly look at how much time it saves me and how useful the features are in my regular work. It may not be perfect in every area, but overall I feel I’m getting reasonable value for the price. Review collected by and hosted on G2.com.

One thing I dislike about Giga is that some features take a little time to understand when you’re using them for the first time. I also feel the overall experience could be smoother in a few areas. It’s not a major issue, but there’s definitely room for improvement. Review collected by and hosted on G2.com.

I really like Giga for how quickly it helps me identify relevant candidates without spending hours on manual searching. The AI-powered candidate matching and sourcing capabilities stand out the most to me. It can analyze job requirements and surface profiles that are a strong match, which helps me build a stronger candidate pipeline faster. It saves time on initial screening, allowing me to focus more on engaging with the best-fit candidates instead of sifting through irrelevant profiles. The initial setup was smooth, and the team was really helpful, providing training to ease the process. Giga is the combination of a clean easy to use UI and strong overall performance. The biggest ROI comes from saving recruiters time and helping us build qualified candidate pipelines faster and the pricing also feels reasonable. The integration with our ATS and other recruiting rools makes it easier to move between sourcing, candidate evaluation, and candidate management without disrupting the workflow. Review collected by and hosted on G2.com.

One area that could be improved is the accuracy and relevance of candidate matches. While Giga is very helpful for speeding up sourcing, sometimes the results can include profiles that are only partially aligned with the job role. More precise matching based on specific skills, years of experience, location, and industry background would make the results even more useful. I would like to see more granular control over candidate matching. For example, the ability to prioritize must-have skills over nice-to-have skills, set a specific minimum and maximum number of years of experience, and apply more precise location preferences such as radius or onsite/remote role. Review collected by and hosted on G2.com.

What I like most about Giga is that it goes beyond basic conversational AI. The platform enables AI agents to understand complex workflows, take action across business systems, and continue improving based on measurable business outcomes. I particularly appreciate the focus on autonomous improvement and KPI-driven performance, rather than simply automating conversations. Review collected by and hosted on G2.com.

What I dislike is that Giga seems geared more toward enterprise customer operations, which could limit its flexibility for broader use cases. Since it’s a relatively newer platform, organizations may also run into a learning curve and may need clearer information around integrations and pricing. Review collected by and hosted on G2.com.

I like how Giga simplifies and streamlines everyday workflows, making them more efficient and reducing the need for repetitive manual work. It's easy to use and helps me complete tasks faster without adding unnecessary complexity. The integration with other productivity and collaboration tools helps keep information connected and reduces the need to switch between different systems. Giga is a useful and easy-to-adopt platform that helps improve productivity and makes managing tasks more efficient. The onboarding process was straightforward, and we were able to get the basic workflows configured without much effort. Review collected by and hosted on G2.com.

I find that one area that could be improved is the overall customization and flexibility. Some workflows may require additional configuration or more advanced options to fit specific use cases. I'd find it helpful if Giga offered more control over how workflows are configured and automated. For example, being able to create custom rules for different scenarios, tailor dashboards to show the metrics that matter most, and set more granular permissions for different users would make it easier to fit Giga into our existing processes. Review collected by and hosted on G2.com.