AI Agents · For operations, support and compliance teams
Ship a production AI agent in 4 to 6 weeks
Custom AI agents for customer service, internal helpdesk, sales ops, document intelligence and compliance. Narrow, production-grade, measured against the metric you care about.
19 years of software delivery. Shipping AI agents since 2024. Vernacular-first. You own the model, the code, and the prompts.
The reality
Hiring faster than tickets is not the strategy
Your Tier-1 queue grows faster than your hires. Training stretches to weeks. Turnover resets the clock. Cost per ticket climbs every quarter. The standard playbook of more agents, longer scripts and night shifts does not scale.
of Tier-1 tickets are repetition
Pattern-match problems that the same human answers a dozen times a day.
internal tickets deflectable
HR and IT queries that a well-scoped internal agent handles before a person gets pulled in.
from scoping to production
One narrow, well-defined agent. Shipped, measured, handed over to your team.
What we build
Five places an AI agent earns its keep
We scope narrow, ship fast, measure honestly. No agent platforms, no multi-agent marketing. One process, one agent, one metric.
Flagship use case
Customer Service Agent
On WhatsApp, phone, email or chat. In your customer's language.
First-line response, triage and escalation. Deflects the 60 to 80% of Tier-1 load that is pattern-match repetition, hands the rest to a human with full context. Vernacular first-class: Hindi, Punjabi, Tamil, plus the usual EU and SEA languages.
Internal operations
Internal Helpdesk Agent
HR Q&A, IT tickets, policy lookup.
Sits in Slack, Teams, WhatsApp or a portal. Answers the repetitive 40 to 60% of internal tickets. Routes the rest with the right context already attached.
Revenue operations
Sales & Lead Ops Agent
Qualify inbound. Schedule calls. Follow up.
CRM-native. Qualifies inbound leads using your own scoring rules, books meetings without a back-and-forth email thread, keeps warm leads alive with human-sounding follow-up until a human takes over.
Unstructured data
Document Intelligence Agent
Invoices, contracts, forms, scanned paperwork.
OCR plus structured extraction. Reads the document, pulls the fields you care about, flags the clauses that need a human, writes the result into your ERP or CRM.
Regulatory
Compliance Agent
GST, DPDP, e-way bill, vendor onboarding.
Tracks the calendar, prepares filings, cross-checks vendor KYC, flags breach-risk patterns. The auditor-facing trail is generated as the agent works, not reconstructed later.
How we build
From scoping call to production agent in four steps
Discovery call (free)
30 minutes. You describe the process. We tell you honestly whether an agent fits, what the narrow first version should scope to, and what would need to be true for it to pay back.
Scoping sprint (1 week)
We define the narrow use case, the success metric, the data sources and the integration surface. Output: a signed scope with a fixed price and a shipping date.
Build (3–5 weeks)
Working agent by end of week 2, shadow mode by week 3, production-ready by week 5. Weekly Friday demos. No disappearing.
Tune & hand over (2 weeks)
Shadow mode, measurement against the success metric, training your team to supervise. Clean handover: source, prompts, evaluation suite, runbook, everything in your accounts.
Proof · Shipped AI work
We have been shipping AI in production since 2024
2024
NLP ticket classifier
An NLP model classifying incoming customer support tickets for a client, improving response times and resource allocation.
2024
Computer vision + OCR for handwritten documents
Detects, aligns and extracts data from handwritten forms using advanced OCR. Shipped into a client workflow.
Under that: 19 years of custom software delivery for IKEA, ABC News, DaVita, Fox40, KFC and more. 240+ mobile apps. 10M+ lines of code. The senior-team discipline that lets us ship a production agent in weeks rather than quarters.
A note we repeat on every first call
AI is a tool, not a religion.
Not every process needs an agent. If the manual baseline takes less than 30 minutes and costs less than ₹500 per event, AI ROI is often negative. If the task has no clean training signal or the consequences of a wrong answer are high-stakes and rare, a rule plus a human reviewer beats a trained model. We will tell you when that's true.
Read the full essay: Honest about AI →Questions
What CTOs and operations heads ask us first
What stack do you build in? +
We build Model-agnostic. We ship on OpenAI, Anthropic, Gemini, and self-hosted open models (Llama, Mistral, Qwen) depending on your data residency, cost and latency constraints. For vernacular we use Sarvam AI and Bhashini where they outperform the global models, which on many Indian languages they now do.
Who owns the model and the code? +
You own the Source code, prompts, evaluation suite, training datasets, cloud accounts, API keys: all in your name, on your infrastructure. No Aquevix lock-in clauses, no background IP claims. Standard with every engagement.
Can it run in our own infrastructure? +
Yes. AWS, Azure, GCP, on-prem, or air-gapped for compliance-sensitive deployments. For orgs in financial services, healthcare, or any regulated industry, we default to self-hosted open models inside your VPC.
What about hallucinations? +
We do not ship open-chat LLMs. Every agent is retrieval-augmented, constrained by your data, with a hard escalation rule when confidence is low. We run shadow mode for the first two weeks in production so you can measure accuracy before letting it talk to customers. If the numbers don't hit the threshold, we tune before handover.
Which languages? +
Hindi, Punjabi, Tamil, Gujarati, Bengali, Marathi and most Indian languages via Sarvam or Bhashini. English, French, German, Spanish, Portuguese, Arabic, Japanese and the usual SEA languages for international clients. We'll confirm the exact language performance for your use case in the scoping call.
What does it cost? +
We provide pricing after the scoping call. Most single-agent engagements land within a predictable band tied to the scope, integrations and language set.
How do you measure success? +
The success metric is defined before we build. Typical metrics: deflection rate (tickets resolved without human handoff), first-response latency, customer satisfaction (CSAT), cost per ticket, accuracy on a held-out evaluation set. We report against the agreed metric every Friday.
Do you build one agent or a platform? +
Usually one narrow agent first. Platforms are where agent projects fail. We ship a production agent that pays back on its own before we talk about multi-agent orchestration. When it's time, the infrastructure is already in your accounts.
Have a process in mind?
Thirty-minute scoping call, no pitch deck. We'll tell you whether an agent fits, what a narrow first version would scope to, and whether we're the right team to build it.
Your move
Tell us what you're trying to do. We'll tell you if we can help.
First conversation is thirty minutes. No pitch deck. You leave with either a clear next step — or an honest "we're not the right team for this". Both are useful.
- Response within one business day
- Mutual NDA available on request
- We'll say no if we're not a fit
19 years · 10M+ lines of code · 240+ mobile apps · IKEA · ABC News · DaVita · SBM Industries