SaaStoAgent

BACKGROUND

Please describe your company and position.

I am the Founder & CEO of futr connect

Describe what your company does in a single sentence.

futr connect is building an AI-powered intelligence platform where professionals create dashboards of intelligent panels that continuously research, organize, and summarize information with agent-driven workflows.

OPPORTUNITY / CHALLENGE

What specific goals or objectives did you hire SaaStoAgent to accomplish?

• Provide consulting on engineering and product development
• Use as much AI and transformative technologies as possible
• Develop entire product built from the ground up to scale quickly and at scale

SOLUTION

How did you find SaaStoAgent?

Personal Introduction from Friend

Why did you select SaaStoAgent over others?

• High ratings
• Pricing fit our budget
• Great culture fit
• Good value for cost
• Referred to me
• Company values aligned

How many teammates from SaaStoAgent were assigned to this project?

6-10 Employees

Describe the scope of work in detail. Please include a summary of key deliverables.

The scope covered the full product and engineering build for FutrConnect Panels, spanning a modern dashboard UI, an agentic backend, and a scalable knowledge layer. SaasToAgent helped implement the core panel types (including Top Trends, Person Spotlight, Company Spotlight, and AI Board Chat), with structured outputs, multi-level summaries, and a refresh system that keeps panels current on schedules and on demand.

A key deliverable was the retrieval layer that grounds answers in user workspace context. Content and uploaded documents were embedded for semantic retrieval using Pinecone, so the system could find relevant items quickly and keep responses consistent with the user’s boards and panels, without making the experience feel “search-heavy.” The platform also included real-time streaming chat, observability for AI operations, and production-focused controls like rate limiting, audit logging, and data isolation.

RESULTS & FEEDBACK

What were the measurable outcomes from the project that demonstrate progress or success?

We saw meaningful improvements in how fast we could generate high-quality intelligence content and how consistently it stayed up to date. Panel generation became repeatable and reviewable, with structured outputs and summaries that worked across many topics. Chat quality improved because answers could pull from the user’s own panel content and attachments first, and only go broader when needed.

We also gained clearer visibility into system performance and cost drivers through tracing and interaction analytics, which made iteration faster and reduced guesswork when tuning prompts, refresh behavior, and retrieval quality.

Describe their project management. Did they deliver items on time? How did they respond to your needs?

SaasToAgent ran the work as a phased product delivery, not a one-time build. Milestones were aligned to working platform slices (panels, chat, retrieval, refresh, observability), and demos were tied to realistic user workflows so we could validate behavior early. When we requested changes, they adjusted the system design and workflow details, not just surface-level prompt tweaks, which helped maintain consistent output quality across panel types.

What was your primary form of communication with SaaStoAgent?

• In-Person Meeting
• Virtual Meeting
• Email or Messaging App

What did you find most impressive or unique about this company?

They're strong at turning an "agentic" concept into something that behaves like a dependable product. The system was designed to be context-aware, traceable, and consistent, with practical guardrails and visibility into what the AI was doing. The result felt like an intelligence workspace that could scale, rather than a demo that only works for a handful of prompts.

Are there any areas for improvement or something SaaStoAgent could have done differently?

Overall, the engagement was very well executed and met our expectations. As the platform continues to mature, the main opportunity lies in expanding its capabilities to support an even broader range of enterprise scenarios. The current foundation is solid and positions SaasToAgent well for long-term scale.

BACKGROUND

Please describe your company and position.

I am the Director of Dcode Station Pty Ltd

Describe what your company does in a single sentence.

We are an Australian stationery brand that creates premium custom-made and refillable journals, and we engaged an AI agent solution to help us manage and convert inbound customer and partnership inquiries more efficiently.

OPPORTUNITY / CHALLENGE

What specific goals or objectives did you hire SaaStoAgent to accomplish?

• We hired SaaStoAgent to build an AI agent for lead handling so we could respond to inbound inquiries faster, qualify potential customers in a more structured way, automate follow-ups, and guide high-intent prospects toward the right next step, whether that was a purchase decision, a custom journal inquiry, or a co-branding conversation. The main objective was to replace fragmented manual handling with a more reliable AI agent workflow.

SOLUTION

How did you find SaaStoAgent?

Clutch Site

Why did you select SaaStoAgent over others?

• High ratings
• Pricing fit our budget
• Good value for cost

How many teammates from SaaStoAgent were assigned to this project?

2-5 Employees

Describe the scope of work in detail. Please include a summary of key deliverables.

SaaStoAgent delivered an AI agent-powered lead handling system tailored to our business workflow. The project began with discovery and workflow mapping, where they identified how inquiries should enter the system, what qualification logic the AI agent should follow, which user intents mattered most, and when a conversation should be escalated internally. They then designed the AI agent interaction flow, built the supporting workflow architecture, and implemented the full lead handling process.

The scope included an AI agent for initial inquiry handling, structured lead qualification, lead capture into our internal workflow, lead scoring logic, automated follow-up for inactive or incomplete conversations, intelligent sharing of relevant product or brand information, internal notifications for qualified opportunities, and a lead tracking dashboard for visibility into stages and outcomes. What stood out was that this was not positioned as a simple chatbot deployment. It was built as an AI agent workflow connected to real business actions and handoff logic.

RESULTS & FEEDBACK

What were the measurable outcomes from the project that demonstrate progress or success?

Within the first month of rollout, the AI agent significantly improved our speed and consistency in handling inbound inquiries. We saw first-response time improve by roughly 75%, lead capture completeness increase to around 80% of inbound conversations, and qualified inquiry progression improve by about 25% compared to our earlier manual process. The AI agent also helped us maintain follow-up coverage on more than 85% of incomplete or inactive conversations, which gave our team much better visibility into opportunities that would previously have been missed.

Describe their project management. Did they deliver items on time? How did they respond to your needs?

Their project management was very strong. They approached the AI agent project in clear phases, starting with discovery, then moving through interaction design, architecture, development, integration, testing, and pilot rollout. They delivered key items on time, communicated clearly throughout, and were responsive whenever we needed refinements to the AI agent flow, qualification logic, or handoff rules. They were organized, practical, and easy to collaborate with.

What was your primary form of communication with SaaStoAgent?

Virtual Meeting

What did you find most impressive or unique about this company?

What impressed us most was their ability to think beyond a chatbot and design a proper AI agent system around the business workflow. They understood that the value was not just in answering messages, but in building an AI agent that could qualify leads, automate follow-ups, support internal handoff, and improve conversion readiness. Their mix of technical depth and business understanding made the whole solution feel much more mature.

Are there any areas for improvement or something SaaStoAgent could have done differently?

Overall, we had a very positive experience. The only area we would suggest improving further is making the AI agent reporting and optimization layer even more benchmark-driven from the start, especially around conversion trends, qualification quality, and monthly performance reviews. That said, this felt more like a minor optimization than a real weakness, and they were always open to feedback.