Agentic AI solutions — goal-driven assistants at the application layer
Agentic AI turns your workflows into goal-driven assistants that plan steps, gather context, call your systems, and complete tasks with human approvals where needed.
We combine knowledge assistants (RAG) with agentic workflows so users get value directly in your app—shorter cycle times, consistent decisions, and happier customers.
What “agentic AI” means in practice
Understands a goal
E.g., “approve a refund under policy.”Plans steps
Gather data, check rules, propose an outcome.Calls tools safely
Reads/writes via approved APIs with least-privilege access.Asks when unsure
Human-in-the-loop for risk or ambiguity.Explains & cites
Shows why a decision was made, with links to sources.Logs everything
Full audit trail, easy to review and export.
Key business benefits of Agentic AI
From answers to completed work
Agents don’t just reply—they collect evidence, check rules, propose a decision, and execute with human sign-off where needed.Faster cycle times, fewer handoffs
Routine approvals, onboarding steps, and case updates move from days to minutes with in-app automations and clear ownership.Consistency & compliance
Policies are enforced by design—least-privilege access, action logs, and citations keep every decision traceable.24/7 service without extra headcount
Agents run nights and weekends, deflecting volume and freeing experts for the hard problems.Measurable ROI & predictable costs
We launch with baselines, evaluation and cost guardrails (caching, routing tiers, budgets) so gains are visible and spend is under control.
Why HyperSense Software?
Proven application-level delivery
Since 2003 we’ve shipped complex software used daily. We put Agentic AI inside your app, where value is felt—copilots, RAG, IDP, approvals and actions.Model & cloud neutrality
OpenAI, Anthropic, Google, AWS Bedrock, Azure, or open source—our model-agnostic stance optimizes for latency, privacy, and cost, and keeps you future-proof.Security & data governance by design
ISO 9001 and ISO/IEC 27001. Encryption in transit/at rest, SSO/RBAC, agent identities & least-privilege, audit trails, human-in-the-loop, and strict data-usage controls.Domain + partnership approach
Engineers collaborate with your operators and leaders to map processes, embed guardrails, and measure impact. After launch, our operate-and-improve loops keep quality high.
High-impact Agentic AI use cases
Knowledge → action assistant
Employees ask in plain English; the agent answers with citations and offers to do the next step (file a ticket, create a case, update a record).Impact: less context switching, fewer errors, faster resolutions.Decision & approval automation
For credit checks, discounts, refunds, access requests: the agent collects evidence, checks policy, proposes a decision, and routes for approval.Impact: shorter turnaround, consistent compliance, full traceability.Customer support copilot (chat/voice)
Drafts replies, verifies identity, executes safe actions (reset, refund, update), and escalates nuanced cases with a clean summary.Impact: higher FCR, lower AHT, better CSAT.Document & case intake (IDP + actions)
Classify → extract → validate → post invoices, claims, contracts; open or update cases with the right metadata.Impact: less manual entry, faster cycle times, audit-ready trails.Onboarding & KYC flows
Gather documents, check completeness, run screenings,create accounts, and schedule follow-ups.Impact: faster onboarding, fewer back-and-forths, cleaner records.Pricing, promotions & recommendations
Suggest next-best action or price change; apply offers or start approval when thresholds are met.Impact: higher conversion and LTV with explainable controls.Revenue operations hygiene
Find missing fields, reconcile quotes/orders, trigger corrections and notify owners.Impact: fewer billing issues, faster order-to-cash.IT & operations runbooks
Auto-triage incidents, run standard steps, gather logs, and prepare the handoff with a concise brief.Impact: faster MTTR, lighter on-call load.Want something else?
We tailor the same agentic patterns to your process—always inside your application, with clear KPIs.
How Agentic AI works
1.
Clarify outcomes and guardrails
We start from your business process and KPI. What should the agent achieve? What must it never do? Where do humans approve?2.
Map tools, data, and policies
Identify systems (CRM/ERP/ITSM), data sources, and rules. Define safe actions and least-privilege access for the agent.3.
Design the in-app experience
Place the agent where users already work—copilot panel, sidebar, or flow step—with clear explanations, citations, and approval states.4.
Build & integrate (model-agnostic)
Connect models (Claude/GPT/Gemini/Bedrock) via an LLM gateway; add retrieval over your content (RAG) and wire approved actions to your APIs.5.
Evaluate & secure
Add quality, faithfulness, safety, and latency checks; enable logging, rate limits, and human-in-the-loop where risk requires it.6.
Pilot & refine
Launch to a small cohort. Measure the KPI, adjust prompts/policies, and tune costs with caching and routing tiers.7.
Scale & operate
Expand usage with a run-book, dashboards, and MLOps routines (monitoring, regression tests, drift checks).
Real-world outcomes
We'll bring quantified examples aligned to your industry during discovery.
Approvals
Routine approvals cut from days to minutes, with consistent policy application.Support
First-contact resolution up; AHT down; agents handle more complex cases.Intake
Finance/claims/case intake throughput rises; exception queues shrink.Revenue ops
Fewer order/billing errors; faster order-to-cash.Risk & compliance
Decisions are explainable, logged, and ready for audit.
What you get
A shipped agentic feature
A shipped agentic feature inside your app (e.g., decision & approval automation, support copilot, IDP + actions).Trusted assistive UX
Assistive UX users trust (states, explanations/citations, approvals).Security & governance framework
Security & governance plan, least-privilege access, audit trails, human-in-the-loop.Evaluation tools
Evaluation suite and dashboards for quality, safety, latency.Cost guardrails and usage insights
Cost guardrails (token budgets, caching, routing tiers) and usage insights.Operational run-book
Run-book & training for operations and a 90-day improvement plan.
Security, governance & cost control
Certifications
ISO/IEC 27001 & ISO 9001 delivery.Privacy by design
Configurable retention, PII/PHI handling, data residency options.Identity & access
SSO/SAML, RBAC, agent identities, least-privilegeAuditability
End-to-end action logs and exportable trails.Evaluation & safety
Faithfulness/quality/latency scoring, guardrails, red-teamingPredictable economics
Prompt caching, routing tiers, usage budgets, dashboards
Insights into AI-powered customer service
Enterprise AI Integration Playbook (Part 3): Infrastructure, Talent & the Path from PoC to Production
Scale AI beyond prototypes with the right data strategy, cross-functional talent, and a modular stack. Compare cloud vs on-prem vs hybrid, and follow the PoC→pilot→production path with reliable MLOps.
Read More
Balancing AI Integration Costs: Build From Scratch or Upgrade Existing Systems?
Discover detailed TCO insights for integrating AI: compare greenfield development with embedding AI into existing infrastructure. Learn cost drivers, ROI, and when each approach makes financial sense.
Read More
Cloud vs. On‑Premise Infrastructure: Comparison Guide for IT Leaders
Cloud adoption soars, yet on-premise remains vital for control, cost, and compliance. This guide weighs CapEx vs OpEx, latency, security, DR, and hybrid models to help IT leaders choose wisely.
Read More
Stay up to date with the latest AI-powered customer service insights
By continuing, you accept the privacy policy.
FAQs
What makes Agentic AI different from a chatbot?
Chat answers questions; agents complete tasks. They collect evidence, check rules, and execute with approvals and audit logs—inside your app.Do we need perfect data to start?
No. We start from your process and KPI, layer in RAG over existing content, and add human-in-the-loop where accuracy matters.Which models and platforms do you support?
We’re model-agnostic and work across AWS Bedrock, OpenAI, Azure, and Gemini—choosing the best tool for each job and keeping swap-ability.How fast can we launch?
Many teams ship a production feature in ≈4 weeks via our AI Feature Sprint.How do you keep our systems secure?
Least-privilege access, encryption, audit logs, and strict model/data-usage controls. Your data is never used to train third-party models without consent.
Contact us and get your project moving
Describe your needs to us and we'll work together to craft the perfect software solution. Tell us your timeframes, your targets or KPIs, and any critical challenges or difficulties. You're at the right place — our team is eager to study and prioritize next steps together with you.Have a project in mind?